Teaching
Courses
At Texas A&M University
- CSCE 481: (Undergraduate) Seminar
- CSCE 482: Senior Capstone Design (S’17, S’16, S’15, F’13, S’13, F’12)
- CSCE 483: Computer System Design (S’14, S’12, S’11, F’10, S’10, S’09, F’08, S’08, F’07, S’07, S’06, S’05, S’04, S’03)
- CSCE 666: Pattern Analysis (S’20)
- CSCE 630: Speech processing (S’11, F’14)
- CSCE 636: Neural Networks (S’10, S’06)
- CSCE 689: Speech and Face Recognition (S’07)
- CSCE 681: Graduate Seminar
Elsewhere
- CEG 499/699: Intelligent Sensor Systems (WSU Spring 2002)
- CEG 498: Design Experience (WSU Spring 2002, with John Gallagher)
- CS 790: Introduction to Pattern Recognition (WSU Winter 2002)
- CEG 411/611: Microprocessor-based System Design (WSU Fall 2001)
- CEG 453/653: Design of Computing Systems (WSU Spring 2000)
- ECE 435: Analog Control Theory (NCSU Summer 1998)
- ECE 465: Computational Intelligence (NCSU Spring 1997, with John Sutton)
Lecture Notes
Pattern recognition
- Introduction to Pattern Recognition
- Review of Statistics and Probability
- Linear algebra and MATLAB
- Bayesian Decision Theory
- Quadratic Classifiers
- Parameter Estimation
- Kernel Density Estimation
- Nearest Neighbors
- Principal Components
- Fisher Linear Discriminants
- Sequential Feature Selection
- Randomized Feature Selection
- Cross-validation
- Mixture Models and EM
- Statistical Clustering
- Competitive Learning
- Linear Discriminant Functions
- Multilayer Perceptrons
- Radial Basis Functions
- MLPs, RBFs and Statistical PR
- Support Vector Machines
- SVMs and Kernel Methods
- Discrete HMMs, Viterbi
- Baum-Welch and Entropic Training
- Ensemble Learning
- Manifold Learning
- Independent Components Analysis
- Kernel PCA/LDA
- Fourier Analysis
Speech processing
- Introduction to Speech Processing
- Speech production and perception
- Organization of speech sounds
- Signals and transforms
- Digital filters
- Short-time Fourier analysis and synthesis
- Linear prediction of speech
- Source estimation
- Cepstral analysis
- Probability, statistics, and estimation theory
- Pattern recognition principles
- Template matching
- Hidden Markov models
- Refinements for HMMs
- Large vocabulary continuous speech recognition
- HTK speech recognition system
- Speaker recognition
- Speech synthesis (front-end)
- Speech synthesis (back end)
- Prosodic modification of speech
- Voice conversion
Intelligent sensor systems
- Course introduction
- Sensor characteristics
- Survey of sensing principles
- Sensor interface circuits
- The ideal op-amp
- Data acquisition I
- LABVIEW examples
- Data acquisition II
- Introduction to pattern analysis
- Dimensionality reduction
- Linear algebra and MATLAB
- Classification
- Validation
- Intelligent sensor systems
- ISS communications
Microprocessor-based system design
- Course introduction
- MC 68000 architecture
- MC68000 instruction set
- Addressing modes
- Program control
- Subroutines I
- Subroutines and stack frames
- C language
- Exception processing
- PI/T timer
- PI/T parallel I/O, part I
- PI/T parallel I/O, part II
- DUART serial I/O, part I
- DUART serial I/O, part II
- Memory and I/O interface
- Address decoding