The full source code and a Windows executable of this tutorial can be downloaded below. Learn more about this unique translation software and how technology such as translation memory and machine translation can help you. SDL game engine tutorials for absolute beginners, written by the lead developer of Seed of Andromeda.
Encoders and decoders codecs Bitstream filters. The SDL helps developers build more secure software by reducing the number and severity of vulnerabilities in software, while reducing development cost. We also support compiling with SDL1 in the same code base, so the migration to pygame 2 is easier. You'll be given code after every few tutorials to carry along We are going to learn basic game development elements, such as Events, game loop, object movement, object collision ,memory management etc and After taking this Tutorial I'll use SDL as the graphics library.
Similarly, include. My comp specs are: Win 8. SDL Development. The above commands will create a directory called build and then build the project. Ignoring the website for sale, a search on the web reveals cs-sdl. Data will arrive at the destination in order and Creating an OpenGL 4. Tutorial 3: Add detail using texture mapping. Mats Dannewitz Linder. For now, we'll build something really simple. It is not a tell all in solving all the problems. To verify that you're ready, try compiling and running the following snippet of code:Greg Sidelnikov of FalloutSoftware.
Control the time step of your game loop. Any similar tutorials? Ok, it is just to teach you the basics of SDL. Installation Debian and Ubuntu. The primary reason being wxWidgets is not a good game programming library, but it is an excellent cross-platform widget toolkit. Tutorial Making Screencaps Code: tutorial The logic of the game can easily be ported to any other programming language.
One of the best tutorials I've found are the inactive jump 'n' run dev tutorials by the late Florian Hufsky. I've already created a console-based text adventure game and am really interested in expanding it into a text-adventure game that has a window and uses interactive media elements. Throughout this series of weekly tutorials I'll be guiding you through SDL 2. From Wikipedia: Simple DirectMedia Layer SDL is a cross-platform, free and open source software multimedia library written in C, that presents a simple interface to various platforms' graphics, sound, and input devices.
Makes it easier to load and render textures. I've left the Visual Studio version off as the process is mostly the same whether it's Visual Studio , or future versions.
In addition it is compared to using 3 separate textures to do the same. It contains instructions that Presentation follows when you run the scenario. Double click and modify the entry to ". Unfortunately, at the time of this writing Raspbian comes with the outdated Overview.
ISBN This tutorial covers better keyboard handling so that more than 1 key can be used at a time. SDL2 Game Tutorials. You'll avoid learning old outdated techniques you shouldn't be using any more unlike many other tutorials. Lesson 0: CMake. It also sets up the OpenGL environment that uses the window, the game loop, and a rotating cube. This example is written using Linux.
Simple Directmedia Layer or SDL is a cross-platform development library designed to provide low level access to audio, keyboard, mouse, joystick, and graphics hardware via OpenGL and Direct3D. SDL2 Tutorials. It also helps with resolving dependencies such as SDL2 , platform specific configurations and much much more. A x window will open, coloured a light shade of blue. Seems like a lot of tutorials want to jump right into OpenGL. It is used by video playback software, emulators, and popular games including Valve 's award winning catalog and many Humble Bundle games.
You can see a simple outline below: Texture Class. Hello all! The original strand off which the new nucleotide sequence is based. Prior to Covid, the majority of faculty had never before taught online, but were instead forced online by Covid To whom it may concern, I currently am taking a biochemistry course online which is much more difficult than in a traditional classroom setting and have use your videos and tutoring in the past, which I have found extremely helpful.
For some odd reason, constructing lipid models using gummy bears and toothpicks felt cheesy, as if I was in elementary school again. There are plenty of potential dystopian futures insert mandatory Gattaca reference here. The highest score of any attempt is applied as the grade for the exam or the assignment in the course.
I was one of the first to complete the capstone with the new format. The other pre-med courses will provide fundamental knowledge for medical schools, such as biochemistry, human anatomy, or microbiology. At Western Governors University—a private, nonprofit, online university—your competence is the ultimate focus of every degree program.
There were many general ed courses I had to retake. But it is concept rich and progressively builds upon acquired learning. Move on to the next when you're passing the quizzes with 80 or above. Make the competency definition behaviorally-based. Set a target for yourself. I had to drop ITT Tech a year ago. In the chaos of modern life, it can often be difficult to provide your patients with the best environment for healing.
Here you can find Biochemistry interview questions with answers and explanation. Being evidence-based practice, the career demands the skills of taking immediate decisions in case of a medical emergency.
Our biochemistry faculty will guide you through the entire semester of biochemistry at the university level. Posted: 1 week ago wgu biochemistry study guide answers provides a comprehensive and comprehensive pathway for students to see progress after the end of each module. Johann N. Program Options for going to Nursing School. Biochemistry as a subject is difficult to learn because of various reasons [9, 19]. First, a phone call to set up taped video response to questions.
Copying DNA in lab. Also explore over similar quizzes in this category. You might not require more become old to spend to go to the books inauguration as competently as search for them. Endochondral ossification is the process by which the embryonic cartilaginous model of most bones contributes to longitudinal growth and is gradually replaced by bone. November 25, As I moved closer to the end of my final term, I was becoming a little worried because I had heard that UFC1 and EZC1 were the most difficult courses for many business undergrad students.
I mean how can you go wrong when your homework consists of making chemical models out of legos or candy… or k-cups ha! On StuDocu you find all the lecture notes, study guides and practice materials for this course I suggest you join the WGU biochemistry group on Facebookthere was a lot of helpful stuff in the files there. This series provides the rich-media introduction to the subject of biochemistry, one chapter per hour in 24 chapters. The binding of the first oxygen molecule has no effect on the binding of the remaining three oxygen molecules E.
Western Governors University Reviews. Choose from different sets of wgu statistics flashcards on Quizlet. At my undergrad, it was a lot of metabolism, cellular processes, and medically based, so it was interesting.
Find a good devotion, or use your bible app to find a study plan. This includes time spent as an undergrad, in medical school, and in residency. Why Biochemistry?
The classes require some busy work at times, but if I didn't understand an assignment, the teachers were available to speak to to help clarify it for me. Lyman, B. Created by. Biochemistry Task 3 A. But to move up in the company, Moore needed a bachelor's degree. Jan 13, Transfer GPA. People who searched for Careers and Occupations List in Physical Sciences found the articles, information, and resources on this page helpful.
Biochem at Birmingham is largely taught by biology with a single module in 1st and 2nd year of pure chemistry. Thesis and non-thesis options are available, depending on a student's interest level in research. December 22, It combines biology and chemistry to investigate the structure, composition, and chemical reactions of substances in living systems.
Join us in our commitment to create pathways to opportunity for all. Mastery of a particular programming language while studying general techniques for managing program complexity, e. Provides practical experience with composing larger systems through several significant programming projects. Course Objectives: Develop a foundation of computer science concepts that arise in the context of data analytics, including algorithm, representation, interpretation, abstraction, sequencing, conditional, function, iteration, recursion, types, objects, and testing, and develop proficiency in the application of these concepts in the context of a modern programming language at a scale of whole programs on par with a traditional CS introduction course.
Student Learning Outcomes: Students will be able to demonstrate a working knowledge of these concepts and a proficiency of programming based upon them sufficient to construct substantial stand-alone programs. Students may take more than one Data Science connector 88 course if they wish, concurrent with or after having taken the C8 course.
Terms offered: Fall Topics will vary semester to semester. See the Computer Science Division announcements. Course does not count toward major requirements, but will be counted in the cumulative units toward graduation. Summer: 6 weeks - 2.
Final exam not required. Terms offered: Fall , Fall , Fall Seminars for group study of selected topics, which will vary from year to year. Intended for students in the lower division. Terms offered: Fall , Fall , Spring A course for lower division students in good standing who wish to undertake a program of individual inquiry initiated jointly by the student and a professor. There are no other formal prerequisites, but the supervising professor must be convinced that the student is able to profit by the program.
Summer: 6 weeks - hours of independent study per week 8 weeks - hours of independent study per week. These include languages for transforming, querying and analyzing data; algorithms for machine learning methods including regression, classification and clustering; principles behind creating informative data visualizations; statistical concepts of measurement error and prediction; and techniques for scalable data processing.
Summer: 8 weeks - 6 hours of lecture, 2 hours of discussion, and 2 hours of laboratory per week. Terms offered: Spring Hardware description languages for digital system design and interactions with tool flows.
Design, implementation, and verification of digital designs. Digital synthesis, partitioning, placement, routing, and simulation for Field-Programmable Gate Arrays. Large digital-system design concepts. Project design component — example, a full processor implementation with peripherals. Student Learning Outcomes: This course is a one-time offering to supplement the EE course offered in the Fall , with a lab and project section that cover the design of larger digital systems on a programmable chip platform FPGA.
Hence the pre-requisite for this course is that a student has taken the EE course in the Fall Terms offered: Spring , Spring , Spring Instruction set architecture, microcoding, pipelining simple and complex.
Memory hierarchies and virtual memory. Processor parallelism: VLIW, vectors, multithreading. Computer Architecture and Engineering: Read Less [-].
Terms offered: Spring , Summer 8 Week Session, Fall The design, implementation, and evaluation of user interfaces. User-centered design and task analysis. Conceptual models and interface metaphors. Usability inspection and evaluation methods. Analysis of user study data. Input methods keyboard, pointing, touch, tangible and input models. Visual design principles. Interface prototyping and implementation methodologies and tools. Students will develop a user interface for a specific task and target user group in teams.
Cryptography, including encryption, authentication, hash functions, cryptographic protocols, and applications. Operating system security, access control. Network security, firewalls, viruses, and worms.
Software security, defensive programming, and language-based security. Case studies from real-world systems. Terms offered: Spring , Fall , Summer 8 Week Session Basic concepts of operating systems and system programming. Utility programs, subsystems, multiple-program systems. Processes, interprocess communication, and synchronization. Memory allocation, segmentation, paging. Loading and linking, libraries. Resource allocation, scheduling, performance evaluation.
Protection, security, and privacy. Terms offered: Fall , Fall , Fall Survey of programming languages. The design of modern programming languages. Principles and techniques of scanning, parsing, semantic analysis, and code generation. Implementation of compilers, interpreters, and assemblers. Overview of run-time organization and error handling. Programming Languages and Compilers: Read Less [-]. Terms offered: Spring , Fall , Fall This course is an introduction to the Internet architecture.
We will focus on the concepts and fundamental design principles that have contributed to the Internet's scalability and robustness and survey the various protocols and algorithms used within this architecture.
Topics include layering, addressing, intradomain routing, interdomain routing, reliable delivery, congestion control, and the core protocols e. Terms offered: Fall , Spring , Fall Ideas and techniques for designing, developing, and modifying large software systems. Function-oriented and object-oriented modular design techniques, designing for re-use and maintainability.
Specification and documentation. Verification and validation. Cost and quality metrics and estimation. Project team organization and management. Students will work in teams on a substantial programming project. Terms offered: Fall Ideas and techniques for designing, developing, and modifying large software systems. Service-oriented architecture, behavior-driven design with user stories, cloud computing, test-driven development, automated testing, cost and quality metrics for maintainability and effort estimation, practical performance and security in software operations, design patterns and refactoring, specification and documentation, agile project team organization and management.
Student Learning Outcomes: Students will learn how to approach and add functionality to a legacy code base; Students will learn how to identify, measure, and resolve maintainability problems in code; Students will learn how to work with nontechnical customers and convert customer requirements into a software plan that can be effort-estimated, built, and deployed to the public cloud, including the use of behavior-driven design, user stories, and velocity; Students will learn how to write automated tests and measure test coverage; Students will learn practical security and performance considerations for SaaS applications.
Introduction to Software Engineering: Read Less [-]. Terms offered: Spring , Spring Open-ended design project enhancing or creating software for real customers in an agile team setting. Teamwork coordination, effective customer meetings, pre- and post-iteration team meetings, running scrums and standups, technical communication. Course Objectives: Students will work in a team to develop new software or enhance existing software for a customer with a real business need.
Student Learning Outcomes: Students will learn how to conduct effective meetings with nontechnical customers and work with their feedback; Students will learn how to coordinate teamwork on developing, testing, and deploying features; and in most cases, how to approach a legacy codebase and add features to it. Students will learn to run a small team including rotation of team roles such as product owner, scrum master, and so on;.
Terms offered: Summer 8 Week Session, Fall , Summer 8 Week Session This course presents ideas and techniques for designing, developing, and modifying large software systems using Agile techniques and tools. Students will learn how to recognize when an appropriate Design Pattern may improve code quality, and refactor code to apply those Design Patterns; Students will learn how to summarize the key architectural elements of RESTful SaaS applications and microservices; Students will learn to articulate the primary differences between Agile and Plan-and-Document methodologies;.
Summer: 8 weeks - 6 hours of web-based lecture and 0 hours of discussion per week. Terms offered: Spring , Fall , Spring Concept and basic techniques in the design and analysis of algorithms; models of computation; lower bounds; algorithms for optimum search trees, balanced trees and UNION-FIND algorithms; numerical and algebraic algorithms; combinatorial algorithms.
Turing machines, how to count steps, deterministic and nondeterministic Turing machines, NP-completeness. Unsolvable and intractable problems. Terms offered: Spring Cryptography or cryptology is the science of designing algorithms and protocols for enabling parties to communicate and compute securely in an untrusted environment e.
Over the last four decades, cryptography has transformed from an ad hoc collection of mysterious tricks into a rigorous science based on firm complexity-theoretic foundations. This modern complexity-theoretic approach to cryptography will be the focus. Undecidable, exponential, and polynomial-time problems. Polynomial-time equivalence of all reasonable models of computation.
Nondeterministic Turing machines. Selected topics in language theory, complexity and randomness. Terms offered: Spring , Fall , Spring Permutations, combinations, principle of inclusion and exclusion, generating functions, Ramsey theory. Expectation and variance, Chebychev's inequality, Chernov bounds. Birthday paradox, coupon collector's problem, Markov chains and entropy computations, universal hashing, random number generation, random graphs and probabilistic existence bounds.
Combinatorics and Discrete Probability: Read Less [-]. Terms offered: Fall , Fall , Fall Algorithms and probabilistic models that arise in various computational biology applications: suffix trees, suffix arrays, pattern matching, repeat finding, sequence alignment, phylogenetics, genome rearrangements, hidden Markov models, gene finding, motif finding, stochastic context free grammars, RNA secondary structure.
There are no biology prerequisites for this course, but a strong quantitative background will be essential. Algorithms for Computational Biology: Read Less [-]. Terms offered: Spring , Spring Deep Networks have revolutionized computer vision, language technology, robotics and control.
They have growing impact in many other areas of science and engineering. They do not however, follow a closed or compact set of theoretical principles. In Yann Lecun's words they require "an interplay between intuitive insights, theoretical modeling, practical implementations, empirical studies, and scientific analyses. Student Learning Outcomes: Students will come to understand visualizing deep networks. Exploring the training and use of deep networks with visualization tools.
Students will learn design principles and best practices: design motifs that work well in particular domains, structure optimization and parameter optimization. Understanding deep networks. Methods with formal guarantees: generative and adversarial models, tensor factorization. Terms offered: Spring Deep Networks have revolutionized computer vision, language technology, robotics and control. Terms offered: Spring , Spring , Summer 8 Week Session Techniques of modeling objects for the purpose of computer rendering: boundary representations, constructive solids geometry, hierarchical scene descriptions.
Mathematical techniques for curve and surface representation. Basic elements of a computer graphics rendering pipeline; architecture of modern graphics display devices. Geometrical transformations such as rotation, scaling, translation, and their matrix representations. Homogeneous coordinates, projective and perspective transformations. Algorithms for clipping, hidden surface removal, rasterization, and anti-aliasing. Scan-line based and ray-based rendering algorithms. Lighting models for reflection, refraction, transparency.
Foundations of Computer Graphics: Read Less [-]. Terms offered: Spring , Fall , Fall Access methods and file systems to facilitate data access. Hierarchical, network, relational, and object-oriented data models. Query languages for models. Embedding query languages in programming languages.
Database services including protection, integrity control, and alternative views of data. High-level interfaces including application generators, browsers, and report writers.
Introduction to transaction processing. Database system implementation to be done as term project. Introduction to Database Systems: Read Less [-]. Terms offered: Fall , Spring , Spring Broad introduction to systems for storing, querying, updating and managing large databases. Computer science skills synthesizing viewpoints from low-level systems architecture to high-level modeling and declarative logic.
System internals, including the complex details of query optimization and execution, concurrency control, indexing, and memory management. More abstract issues in query languages and data modeling — students are exposed to formal relational languages, SQL, full-text search, entity-relationship modeling, normalization, and physical database design.
Summer: 8 weeks - 6 hours of web-based lecture and 2 hours of discussion per week. Terms offered: Spring , Fall , Summer 8 Week Session Ideas and techniques underlying the design of intelligent computer systems.
Topics include search, game playing, knowledge representation, inference, planning, reasoning under uncertainty, machine learning, robotics, perception, and language understanding. Introduction to Artificial Intelligence: Read Less [-]. Terms offered: Spring , Fall , Spring Theoretical foundations, algorithms, methodologies, and applications for machine learning. Topics may include supervised methods for regression and classication linear models, trees, neural networks, ensemble methods, instance-based methods ; generative and discriminative probabilistic models; Bayesian parametric learning; density estimation and clustering; Bayesian networks; time series models; dimensionality reduction; programming projects covering a variety of real-world applications.
Introduction to Machine Learning: Read Less [-]. Terms offered: Fall , Fall , Spring This multidisciplinary course provides an introduction to fundamental conceptual aspects of quantum mechanics from a computational and informational theoretic perspective, as well as physical implementations and technological applications of quantum information science.
Basic sections of quantum algorithms, complexity, and cryptography, will be touched upon, as well as pertinent physical realizations from nanoscale science and engineering. Terms offered: Spring , Fall , Spring Topics will vary semester to semester. Terms offered: Spring , Fall , Spring Topics include electronic community; the changing nature of work; technological risks; the information economy; intellectual property; privacy; artificial intelligence and the sense of self; pornography and censorship; professional ethics.
Students will lead discussions on additional topics. Terms offered: Fall , Fall , Spring Topics include electronic community; the changing nature of work; technological risks; the information economy; intellectual property; privacy; artificial intelligence and the sense of self; pornography and censorship; professional ethics. Students may lead discussions on additional topics.
Credit Restrictions: Student will receive no credit for H after taking or C Terms offered: Fall , Fall , Fall Thesis work under the supervision of a faculty member. To obtain credit the student must, at the end of two semesters, submit a satisfactory thesis to the Electrical Engineering and Computer Science department archive. A total of four units must be taken.
The units many be distributed between one or two semesters in any way. HA-HB count as graded technical elective units, but may not be used to satisfy the requirement for 27 upper division technical units in the College of Letters and Science with a major in Computer Science. Terms offered: Spring , Spring , Fall Thesis work under the supervision of a faculty member. Terms offered: Spring , Fall , Spring Group study of selected topics in Computer Sciences, usually relating to new developments.
Terms offered: Fall , Spring , Fall Supervised independent study. Enrollment restrictions apply. Credit Restrictions: Enrollment is restricted; see the Introduction to Courses and Curricula section of this catalog. Terms offered: Fall , Fall , Spring The Freshman Seminar Program has been designed to provide new students with the opportunity to explore an intellectual topic with a faculty member in a small seminar setting.
Freshman seminars are offered in all campus departments, and topics may vary from department to department and semester to semester. Terms offered: Fall A Berkeley Electrical Engineering and Computer Sciences degree opens the door to many opportunities, but what exactly are they? Graduation is only a few years away and it's not too early to find out.
In this seminar students will hear from practicing engineers who recently graduated. What are they working on? Are they working in a team? What do they wish they had learned better? How did they find their jobs? Terms offered: Spring , Fall , Fall Freshman and sophomore seminars offer lower division students the opportunity to explore an intellectual topic with a faculty member and a group of peers in a small-seminar setting.
Terms offered: Fall , Summer 8 Week Session, Spring This course serves as an introduction to the principles of electrical engineering, starting from the basic concepts of voltage and current and circuit elements of resistors, capacitors, and inductors. Circuit analysis is taught using Kirchhoff's voltage and current laws with Thevenin and Norton equivalents. Operational amplifiers with feedback are introduced as basic building blocks for amplication and filtering.
Digital logic gates and design using CMOS as well as simple flip-flops are introduced. Speed and scaling issues for CMOS are considered. The course includes as motivating examples designs of high level applications including logic circuits, amplifiers, power supplies, and communication links.
Credit Restrictions: Students will receive no credit for 42 after taking 40 or Introduction to Digital Electronics: Read Less [-]. Terms offered: Spring , Spring , Fall Electronics has become pervasive in our lives as a powerful technology with applications in a wide range of fields including healthcare, environmental monitoring, robotics, or entertainment.
This course teaches how to build electronic circuits that interact with the environment through sensors and actuators and how to communicate wirelessly with the internet to cooperate with other devices and with humans. In the laboratory students design and build representative samples such as solar harvesters, robots, that exchange information with or are controlled from the cloud. Course Objectives: Electronics has become a powerful and ubiquitous technology supporting solutions to a wide range of applications in fields ranging from science, engineering, healthcare, environmental monitoring, transportation, to entertainment.
The objective of this course is to teach students majoring in these and related subjects how to use electronic devices to solve problems in their areas of expertise. Through the lecture and laboratory, students gain insight into the possibilities and limitations of the technology and how to use electronics to help solve problems. Students learn to use electronics to interact with the environment through sound, light, temperature, motion using sensors and actuators, and how to use electronic computation to orchestrate the interactions and exchange information wirelessly over the internet.
Student Learning Outcomes: Deploy electronic sensors and interface them to microcontrollers through digital and analog channels as well as common protocols I2C, SPI , Design, build and test electronic devices leveraging these concepts. Interact with the internet and cloud services using protocols such as http, MQTT, Blynk, Interface DC motors, steppers and servos to microcontrollers, Represent information with voltage, current, power, and energy and how to measure these quantities with laboratory equipment, To use and program low-cost and low-power microcontrollers for sensing, actuation, and information processing, and find and use program libraries supporting these tasks Understand and make basic low-pass and high-pass filters, Wheatstone bridge etc.
Use electronics to sense and actuate physical parameters such as temperature, humidity, sound, light, and motion,. Electronics for the Internet of Things: Read Less [-].
Terms offered: Spring , Fall , Spring Sophomore seminars are small interactive courses offered by faculty members in departments all across the campus. Sophomore seminars offer opportunity for close, regular intellectual contact between faculty members and students in the crucial second year.
The topics vary from department to department and semester to semester. Enrollment limited to 15 sophomores. Terms offered: Fall , Fall , Fall Group study of selected topics in electrical engineering, usually relating to new developments. Terms offered: Spring , Fall , Spring Supervised independent study and research for students with fewer than 60 units completed.
Prerequisites: Freshman or sophomore standing and consent of instructor. Minimum GPA of 3. Terms offered: Spring , Fall , Spring This course covers the fundamental circuit and device concepts needed to understand analog integrated circuits. Two port small-signal amplifiers and their realization using single stage and multistage CMOS building blocks are discussed.
Sinusoidal steady-state signals are introduced and the techniques of phasor analysis are developed, including impedance and the magnitude and phase response of linear circuits. The frequency responses of single and multi-stage amplifiers are analyzed. Differential amplifiers are introduced. Microelectronic Devices and Circuits: Read Less [-]. Terms offered: Fall , Fall , Fall An introduction to the kinematics, dynamics, and control of robot manipulators, robotic vision, and sensing.
The course covers forward and inverse kinematics of serial chain manipulators, the manipulator Jacobian, force relations, dynamics, and control. It presents elementary principles on proximity, tactile, and force sensing, vision sensors, camera calibration, stereo construction, and motion detection.
The course concludes with current applications of robotics in active perception, medical robotics, and other areas. This course will cover dynamics and control of groups of robotic manipulators coordinating with each other and interacting with the environment.
Concepts will include an introduction to grasping and the constrained manipulation, contacts and force control for interaction with the environment. We will also cover active perception guided manipulation, as well as the manipulation of non-rigid objects. Throughout, we will emphasize design and human-robot interactions, and applications to applications in manufacturing, service robotics, tele-surgery, and locomotion.
Terms offered: Fall , Fall , Fall Power conversion circuits and techniques. Characterization and design of magnetic devices including transformers, reactors, and electromagnetic machinery. Characteristics of bipolar and MOS power semiconductor devices. Applications to motor control, switching power supplies, lighting, power systems, and other areas as appropriate. Terms offered: Spring , Spring , Spring Review of static electric and magnetic fields and applications; Maxwell's equations; transmission lines; propagation and reflection of plane waves; introduction to guided waves, microwave networks, and radiation and antennas.
Minilabs on statics, transmission lines, and waves. Explanation of cellphone antennas, WiFi communication, and other wireless technologies. Electromagnetic Fields and Waves: Read Less [-]. Terms offered: Fall , Fall , Fall Fundamental principles of optical systems. Geometrical optics and aberration theory. Stops and apertures, prisms, and mirrors.
Diffraction and interference. Optical materials and coatings. Radiometry and photometry. Basic optical devices and the human eye. The design of optical systems. Lasers, fiber optics, and holography. A deficient grade in Electrical Engineering may be removed by taking Electrical Engineering Introduction to Optical Engineering: Read Less [-]. Terms offered: Spring , Fall , Spring Continuous and discrete-time transform analysis techniques with illustrative applications.
Linear and time-invariant systems, transfer functions. Fourier series, Fourier transform, Laplace and Z-transforms. Sampling and reconstruction. Solution of differential and difference equations using transforms. Frequency response, Bode plots, stability analysis.
Illustrated by analysis of communication systems and feedback control systems. Terms offered: Spring , Fall , Fall Introduction to the basic principles of the design and analysis of modern digital communication systems.
Topics include source coding, channel coding, baseband and passband modulation techniques, receiver design, and channel equalization.
Applications to design of digital telephone modems, compact disks, and digital wireless communication systems. Terms offered: Spring , Spring , Spring This course focuses on the fundamentals of the wired and wireless communication networks. The course covers both the architectural principles for making these networks scalable and robust, as well as the key techniques essential for analyzing and designing them.
The topics include graph theory, Markov chains, queuing, optimization techniques, the physical and link layers, switching, transport, cellular networks and Wi-Fi. Introduction to Communication Networks: Read Less [-]. Digital signal processing topics: flow graphs, realizations, FFT, chirp-Z algorithms, Hilbert transform relations, quantization effects, linear prediction. Digital filter design methods: windowing, frequency sampling, S-to-Z methods, frequency-transformation methods, optimization methods, 2-dimensional filter design.
Terms offered: Spring , Fall , Spring , Fall Analysis and synthesis of linear feedback control systems in transform and time domains. Control system design by root locus, frequency response, and state space methods.
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