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Communications and Signal Processing Applications
OVERVIEW
CEA CAPA Partner Institution: University of Galway
Location: Galway, Ireland
Primary Subject Area: Electrical Engineering
Instruction in: English
Course Code: EE444
Transcript Source: Partner Institution
Course Details: Level 400
Recommended Semester Credits: 2.5
Contact Hours: 36
DESCRIPTION
Applications of Digital Signal Processing (DSP) and communications technology, including: multirate DSP, speech processing, adaptive filters, biomedical signal processing, Security algorithms, infrastructure and protcols, security threats, topics in: networking for financial trading environments, Software Defined Networking, mobile network and services evolution, webscale service deployment and data analytics, mobile broadband evolution
Learning Outcomes
1. Analyse a multi-rate DSP system, in particular, determine the spectral characteristics of signals at different points in the system, and design multi-rate DSP systems to change the sampling rate of a signal by means of an arbitrary rational factor.
2. For discrete-time speech signals, develop DSP algorithms to extract useful features from the signal, in particular energy, zero-crossing count, pitch information, and LPC coefficients, and describe how these features may be used in practical applications like speech recognition
3. Design adaptive filter systems using the LMS algorithm, for use in problems in system identification.
4. Design filters suitable for use in biomedical signal processing applications, in particular removal of narrowband noise.
5. Characterise security threats and outline methods of implementing security
6. Analyse and implement algorithms for encryption, authentication and message integrity
7. Analyse and critique impact and evolution of cloud technologies and data analytics on mobile and web services
8. Analyse and critique the Software Defined Networking paradigm
9. Analyse and advise on networking technologies specifically for financial trading environments
Learning Outcomes
1. Analyse a multi-rate DSP system, in particular, determine the spectral characteristics of signals at different points in the system, and design multi-rate DSP systems to change the sampling rate of a signal by means of an arbitrary rational factor.
2. For discrete-time speech signals, develop DSP algorithms to extract useful features from the signal, in particular energy, zero-crossing count, pitch information, and LPC coefficients, and describe how these features may be used in practical applications like speech recognition
3. Design adaptive filter systems using the LMS algorithm, for use in problems in system identification.
4. Design filters suitable for use in biomedical signal processing applications, in particular removal of narrowband noise.
5. Characterise security threats and outline methods of implementing security
6. Analyse and implement algorithms for encryption, authentication and message integrity
7. Analyse and critique impact and evolution of cloud technologies and data analytics on mobile and web services
8. Analyse and critique the Software Defined Networking paradigm
9. Analyse and advise on networking technologies specifically for financial trading environments
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