|
|
|
|
|
|
|
|
|
|
Course Criteria
Add courses to your favorites to save, share, and find your best transfer school.
-
3.00 Credits
Prerequisites: CS 04222 and MATH 01131 and CS 07210 This is an advanced course in the theoretical foundations of computer science, building on the introduction provided in the Foundations of Computer Science course. It studies models of computers, such as finite automata and Turing machines, formal languages, and computability, as well as the fundamentals of complexity theory and NP-completeness.
-
3.00 Credits
Prerequisites: MATH 03160 and CS 04222 and CS 07210 AI studies methods for programming "intelligent" behavior in computers. Students study the data representation methods and algorithms used in AI, and survey research areas such as puzzle solving, game-playing, natural language processing, expert systems, and learning. In addition to readings, discussion, and problem solving in AI, students will be expected to program in one of the languages commonly used in AI, such as LISP or Prolog.
-
3.00 Credits
This class will introduce a broad spectrum of pattern recognition algorithms along with various statistical data analysis and optimization procedures that are commonly used in such algorithms, with particular emphasis to engineering applications. Although mathematically intensive, pattern recognition is nevertheless a very application driven field. This class will therefore cover both theoretical and practical aspects of pattern recognition, Bayes decision theory for optimum classifiers, density estimation techniques, discriminant analysis, basic optimization techniques, introduction to basic neural network structures, unsupervised clustering techniques and more state of the art algorithm independent techniques.
-
3.00 Credits
Students are assigned projects in a professional environment.
-
2.00 Credits
Prerequisites: CS 04103 and MATH 01131 and PHYS 02200 and MATH 01235 Covers basic network principles, network laws and analysis methods, including steady-state and transient responses of passive networks, with independent and dependent sources. Op amps are covered as examples of active electronic networks. Computer-aided analysis and simulation tools are presented as methods to augment network analysis and design.
-
2.00 Credits
Prerequisites: ECE 09201 Minimum Grade of C Extends network analysis principles including ac sources, transformers, and polyphase networks. The Laplace transform is developed as a method for obtaining the transient and steady-state response of a network. The frequency response of a transfer function is analyzed using Bode plots. The Fourier transform technique is used to determine the response of networks to periodic inputs. Computer-aided analysis and simulation tools are presented as methods to augment network analysis and design.
-
3.00 Credits
Prerequisites: CS 04103 and ECE 09201 Minimum Grade of C The first course in digital systems covering boolean algebra, switching theory, minimization, asynchronous and synchronous network design, hardware design using state equations in a simulation and development environment. The course also treats applications of digital system design.
-
3.00 Credits
Prerequisites: ECE 09443 Minimum Grade of C The second course in digital systems covering principles of computer systems design including hardware and software. The course also treats applications of computer design.
-
2.00 Credits
Prerequisites: ECE 09202 Minimum Grade of C and PHYS 02200 and MATH 01236 The first course in engineering electromagnetics covering applications of electrostatics, magnetostatics and quasi-statics in contemporary electrical engineering practice. The course also covers numerical modeling of electromagnetic systems using appropriate software.
-
2.00 Credits
Prerequisites: ECE 09202 Minimum Grade of C and MATH 01236 and ECE 09301 Minimum Grade of C The second course in engineering electromagnetics covering applications of electromagnetic wave propagation in contemporary electrical engineering practice. The course also covers numerical modeling of electromagnetic systems using appropriate software.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Privacy Statement
|
Terms of Use
|
Institutional Membership Information
|
About AcademyOne
Copyright 2006 - 2025 AcademyOne, Inc.
|
|
|