- Advanced Transform Methods
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Advanced Transform Methods
Time-frequency transforms are an important tool in the analysis and processing of signals and images. These transforms include the Fourier transform, spectrogram, discrete cosine transform, wavelet transform, and Wigner-Ville distribution. This course will introduce these various transforms and explore how they are suitable for different signal and image processing applications.
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Advanced Transform Methods
Summary:
Time-frequency transforms are an important tool in the analysis and processing of signals and images. These transforms include the Fourier transform, spectrogram, discrete cosine transform, wavelet transform, and Wigner-Ville distribution. This course will introduce these various transforms and explore how they are suitable for different signal and image processing applications.
Credits:
15.0
Pre-requisites:
ELE502 or ELEM020
Aims:
This course aims to introduce transform and sub-band techniques as a pre-cursor to compression and other applications. It is the first step beyond the fundamentals of Digital Signal processing.
Objectives:
Recall a range of joint time-frequency transforms.
Discuss the relative merits of different transforms.
Employ the common mathematical framework underlying many transform methods.
Derive various properties of different transforms.
Use high performance mathematical visualization software (e.g. Matlab) to implement these transforms.
Apply these transforms to signal and image processing problems, such as compression or denoising.
Core Skills:
Analyse information using mathematical models
Books:
A Wavelet Tour of Signal Processing, Third Edition: The Sparse Way, by S.G. Mallat; Academic Press, ISBN: 13: 978-0-12-374370-1
- Fundamentals of DSP
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Fundamentals of DSP
The purpose of this module is to introduce the general topic of Digital Signal Processing and bring students up to a common level. Students are first introduced to the behaviour of simple filters as LTI systems, represented by difference equations. Frequency response of these systems leads into the study of Discrete Fourier Transform and simple Spectral Analysis. There follow sections on designing the coefficients of LTI systems so they can be programmed to perform as filters to prescribed magnitude specifications.
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Fundamentals of DSP
Summary:
The purpose of this module is to introduce the general topic of Digital Signal Processing and bring students up to a common level. Students are first introduced to the behaviour of simple filters as LTI systems, represented by difference equations. Frequency response of these systems leads into the study of Discrete Fourier Transform and simple Spectral Analysis. There follow sections on designing the coefficients of LTI systems so they can be programmed to perform as filters to prescribed magnitude specifications.
Credits:
15.0
Aims:
This module will introduce the general topic of Digital Signal Processing and bring students from diverse backgrounds up to a common level for Msc studies in DSP. This is done through lectures and an intensive laboratory programme.
Objectives:
Describe the basic operations of DSP of addition, multiplication and memory/delay.
Employ these simple operators in combination to perform useful tasks such as filtering and spectral analysis.
Analyse simple filter structures both analytically and empirically (using Matlab).
Design digital filters to meet specifications.
Formulate the parameters of a spectral analysis system to obtain adequate resolution for the given task.
Core Skills:
This course is designed to bring all MSc DSP students up to a common level.
All subsequent Signal processing courses in the programme are either directly or indirectly dependent on ELEM020.
Books:
Digital Signal Processing: a computer based approach by Sanjit Mitra; McGraw-Hill 2005; ISBN 0071244670
- Real-Time DSP
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Real-Time DSP
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Real-Time DSP
Credits:
15.0
Pre-requisites:
Digital signal processing, signals and systems
Aims:
1. To introduce students to DSP chips and common accompanying hardware components by familiarizing them with the Texas Instruments C6711 evaluation module.
2. To allow students to work with the software environment provided by DSP chip manufacturers and to explore the additional software constructs and mechanisms provided to allow the development of real-time applications.
3. For students to develop an understanding of whether an application must be executable in real-time and, if so, what constraints this imposes on the design of the software and the use of the hardware.
4. To encourage students to fully use and help them to interpret the large body of documentation, sample code and user manuals that exists for the topics this course will encompass.
5. To introduce students, by demonstration, platform specific and DSP chip specific debugging techniques and to appreciate the problems encountered when debugging real-time applications.
6. To positively encourage independent learning and synthesis of ideas through project work.
Objectives:
1. To introduce students to DSP chips and common accompanying hardware components by familiarizing them with the Texas Instruments C6711 evaluation module.
o Students should become very familiar with the technology, its properties, strengths and weaknesses.
o Students should be aware of the choices available when choosing a processor, and when to select a DSP over an ASIC or a general purpose processor.
2. To allow students to work with the software environment provided by DSP chip manufacturers and to explore the additional software constructs and mechanisms provided to allow the development of real-time applications.
o Students must be able to demonstrate a working knowledge of the Texas Instruments ‘Code Composer Studio’ software package.
o Students must be able to utilize the real-time specific functionality of the software environment.
3. For students to develop an understanding of whether an application must be executable in real-time and, if so, what constraints this imposes on the design of the software and the use of the hardware.
o Students must be able to differentiate between real-time and non-real-time applications.
o Students must appreciate how the real-time requirement has shaped the development of DSP chips and will shape their applications.
4. To encourage students to fully use and help them to interpret the large body of documentation, sample code and user manuals that exists for the topics this course will encompass.
o Students are expected to use the user manuals supplied with the evaluation module to complete assignments.
o Students are expected to identify when to write original applications and when to draw from existing material.
5. To introduce students, by demonstration, to platform specific and DSP chip specific debugging techniques and to appreciate the problems encountered when debugging real-time applications.
o Students must successfully solve problems in a laboratory environment.
6. To positively encourage independent learning and synthesis of ideas through project work.
o Students will complete a project of their own specification that is expected to demonstrate an understanding of most (if not all) of the aims and learning outcomes of this course.
o Students must demonstrate the ability to critically appraise their own work.
o Students are expected to present results in an unambiguous fashion and to appreciate why this is particularly difficult in the fields of both real-time applications and of audio or video applications.
Books:
C6x-Based Digital Signal Processing by N. Kehtarnavaz and B. Simsek; Prentice Hall 2000; ISBN 0130883107
- Music and Speech Processing
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Music and Speech Processing
This course aims to introduce students to the application of Digital Signal Processing to music and speech.
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Music and Speech Processing
Summary:
This course aims to introduce students to the application of Digital Signal Processing to music and speech.
Credits:
15.0
Pre-requisites:
ELE502, ELEM020, ELEM018
Aims:
The application-oriented nature of the syllabus will reinforce the theory learned in other courses through lectures and laboratories.
Objectives:
Describe the physiology and physics involved in sound production and perception.
Demonstrate how various fundamental concepts in Digital Signal Processing can be combined into systems, like a Digital Power Amplifier.
Demonstrate how higher level processing components are constructed from lower level ones.
Discuss how compression of speech and of music, though similar, have different requirements.
Propose specific compressors for specific applications.
Identify latest innovations in this area involving delivery formats such as Internet and DVD.
Position their acquired knowledge in a commercial context.
Core Skills:
Students will be able to evaluate and design complex signal processing systems.
Books:
Speech and Audio Signal Processing: Processing and Perception of Speech and Music by B.Gold and N.Morgan; John Wiley and Sons 1999; ISBN 0471351547
- Machine Learning
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Machine Learning
This course covers methods for machine learning from signals and data, including statistical pattern recognition methods, neural networks, and clustering.
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Machine Learning
Summary:
This course covers methods for machine learning from signals and data, including statistical pattern recognition methods, neural networks, and clustering.
Credits:
15.0
Aims:
The aim of the course is to give students an understanding of machine learning methods, including pattern recognition, clustering and neural networks, and to allow them to apply such methods in a range of areas.
Objectives:
Recall a range of machine learning techniques and algorithms, including neural networks and statistical methods
Use concepts from probability theory in machine learning
Derive and analyse properties of machine learning methods
Discuss the relative merits of different machine learning techniques and approaches
Apply machine learning methods to the analysis of signals and data
Books:
Pattern Recognition and Machine Learning by C. M. Bishop; Springer 2006; ISBN 0387310738
- Mobile Services
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Mobile Services
Basic mobile services for computer and communication resource poor environments that are accessed over a wireless network and independent of specific devices and platforms are first considered before this model is extended to the realm of ubiquitous or pervasive computing to include context-aware interaction, automated sensing and capture, the disappearing computer and ambient intelligence.
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Mobile Services
Summary:
Basic mobile services for computer and communication resource poor environments that are accessed over a wireless network and independent of specific devices and platforms are first considered before this model is extended to the realm of ubiquitous or pervasive computing to include context-aware interaction, automated sensing and capture, the disappearing computer and ambient intelligence.
Credits:
15.0
Pre-requisites:
ELEM002 or ELEM039
Aims:
To enable students to:
Understand the characteristics, motivation and opportunities for developing mobile user services
Appreciate the strengths and weaknesses of developing mobile services using different software architectures.
Understand the development process for creating and maintaining mobile services
Understand the e-commerce and management issues associated with rapid development and deployment of mobile services
Objectives:
Describe the basic principles of mobile services
Identify the basic components of mobile services and explain how they work
Explain the key issues associated with constructing mobile services and the main approaches taken to developing such services.
Design and create an application using contemporary middleware
Explain the main application areas for mobile services.
Core Skills:
Analyse requirements and design a system (from assignment).
Create a well-written report.
Books:
Poslad S. (2009) Ubiquitous Computing: Smart Devices, Environments and Interaction, Wiley, ISBN-13 9780470035603
- Introduction to Computer Vision
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Introduction to Computer Vision
New module under development for 2012/13. Information pertaining to this module will appear once approved.
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Introduction to Computer Vision
Summary:
New module under development for 2012/13. Information pertaining to this module will appear once approved.
Credits:
15.0
Aims:
New module under development for 2012/13. Information pertaining to this module will appear once approved.
Objectives:
New module under development for 2012/13. Information pertaining to this module will appear once approved.
Core Skills:
New module under development for 2012/13. Information pertaining to this module will appear once approved.
- Sensors and Internet of Things
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Sensors and Internet of Things
New module under development for 2012/13. Information pertaining to this module will appear once approved.
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Sensors and Internet of Things
Summary:
New module under development for 2012/13. Information pertaining to this module will appear once approved.
Credits:
15.0
Aims:
New module under development for 2012/13. Information pertaining to this module will appear once approved.
Objectives:
New module under development for 2012/13. Information pertaining to this module will appear once approved.
Core Skills:
New module under development for 2012/13. Information pertaining to this module will appear once approved.
Extra Costs:
New module under development for 2012/13. Information pertaining to this module will appear once approved.
