Course GitHub: https://github.com/k-m-nog/CPE322

This course addresses the general topic of selection, evaluation and design of a project concept, emphasizing the principles of team-based projects and the stages of project development. Techniques to acquire information related to the state-of-the-art concepts and components impacting the project, evaluation of alternative approaches and selection of viable solutions based on appropriate cost factors, presentation of proposed projects at initial, intermediate and final stages of development and related design topics. Students are encouraged to use this experience to prepare for the senior design project courses.

The objective of this course is to introduce current techniques in securing IP and multimedia networks. Topics under IP security will include classic cryptography, Diffie-Hellman, RSA, end-to-end authentication, Kerberos, viruses, worms and intrusion detection. Topics from multimedia will include steganography, digital watermarking, covert channels, hacking, jamming, security features in MPEG-4, secure media streaming, wireless multimedia, copy control and other mechanisms for secure storage and transfer of audio, image and video data.

Introduction to the theory and design of digital signal processing systems. Include sampling, linear convolution, impulse response, and difference equations; discrete-time Fourier transform, DFT/FFT, circular convolution, and Z-transform; frequency response, magnitude, phase and group delays; ideal filters, linear-phase FIR filters, all-pass filters, minimum phase and inverse systems; digital processing of continuous-time signals.

This is a course on more complex data structures, and algorithm design and analysis, using the C++ language. Topics include: advanced and/or balanced search trees; hashing; further asymptotic complexity analysis; standard algorithm design techniques; graph algorithms; complex sort algorithms; and other “classic” algorithms that serve as examples of design techniques.

Development of deterministic and non-deterministic models for physical systems, engineering applications and simulation tools for deterministic and non-deterministic systems. Case studies and projects.

Students learn a set of Engineering Economic techniques that serve as powerful tools to aid in the design, implementation and continued improvement of any engineering project or process. The primary goal of this course is to help students develop an ability to make sound economic decisions, thereby facilitating effective evaluation and selection of alternative technical, design, and engineering solutions. In this course students will be exposed to the analysis of financial data, the concept of interest rates, the time value of money, economic analysis using the three worths, internal rate of return and benefit cost analysis. Furthermore, the student will gain a comprehensive knowledge about advanced engineering economy topics such as depreciation, capital cost and recovery, after tax analysis, inflation, sensitivity analysis, risk analysis and simulation. Laboratory exercises include the use of spreadsheets to solve engineering economy problems and a series of labs that parallel the lecture portion of the course