The matters discussed during the lectures and exercises are required in the exam. In addition to the distributed course material (lecture slides and exercise answers) the subjects can be studied from the following sources:

INTRODUCTION:

• Schalkoff, chapter 1 (introduction)
• Theodoridis et al,
  • chapter 1 (introduction);
  • chapter 5 (feature selection), sections 5.1-5.2.3, 5.4-5.5, 5.6-5.6.2
  • chapter 10 (evaluation), sections 10.1-10.3

STATISTICAL PATTERN RECOGNITION:

• Schalkoff, chapter 2
• Theodoridis et al, chapter 2, sections 2.1-2.4

ESTIMATION OF PROBABILITY DISTRIBUTIONS:

• Schalkoff, chapter 3
• Theodoridis et al, chapter 2, sections 2.5-2.5.4, 2.6

LINEAR CLASSIFIERS:

• Schalkoff, chapter 4
• Theodoridis et al, chapter 3, sections 3.1-3.5.2

NONLINEAR CLASSIFIERS:

• Theodoridis et al, chapter 4 sections 4.12-4.15,
• A tutorial on Support Vector Machines for Pattern Recognition, http://svm.research.bell-labs.com. If the link above is nonfunctional, a copy of the paper can also be obtained through www.kernel-machines.org, or directly by following this link.

NEURAL NETWORK - BASED METHODS:

• Schalkoff, chapter 10, chapter 12
• Theodoridis et al, chapter 4, sections 4.1-4.8, 4.11

SYNTACTIC AND STRUCTURAL METHODS:

• Schalkoff,
  • chapter 6 (formal languages);
  • chapter 7 (parsing);
  • chapter 8 (graphs);
• Syntactic Pattern Recognition and Application, King Sun Fu,
  • chapter 1 (introduction), sections 1.1-1.2;
  • chapter 2 (formal languages and automatons), sections 2.1-2.5;
  • chapter 5 (parsing), sections 5.1-5.3

UNSUPERVISED LEARNING AND CLUSTERING:

• Schalkoff,
  • chapter 5;
  • chapter 13 (SOM)
• Theodoridis et al,
  • chapter 11 (introduction), sections 11.1-11.1.1, 11.1.3;
  • chapter 12 (sequental algorithms), sections 12.1-12.3;
  • chapter 13 (hierarchical methods), sections 13.1-13.2.2, 13.2.5, 13.4;
  • chapter 14 (methods based on function optimization), sections 14.1, 14.5-14.6;
  • chapter 15 (methods based on competition), section 15.2.1, sections 15.3-15.3.2, 15.3.5-15.3.6

All the subjects are not in one book; in the books the subjects have sometimes been presented with a much wider scope than in the course. It is sufficient to know the subjects in the scope they were presented in in the lectures and exercises!