The book provides an excellent class-tested material for graduate courses in artificial neural networks. It is completely self-contained and includes also thorough introduction to the discussed discipline-specific areas of mathematics...Therefore, this book represents a good reference source of applicable ideas for a wide audience including students, researchers and application specialists as well.

• I INTRODUCTION TO NEURAL NETWORKS; II ADVANCED NEURAL NETWORKS; III INFORMATION THEORY AND NEURAL NETWORKS; IV MACROSCOPIC ANALYSIS OF DYNAMICS; V EQUILIBRIUM STATISTICAL MECHANICS OF NEURAL NETWORKS; APPENDICES; REFERENCES

The book provides an excellent class-tested material for graduate courses in artificial neural networks. It is completely self-contained and includes also thorough introduction to the discussed discipline-specific areas of mathematics...Therefore, this book represents a good reference source of applicable ideas for a wide audience including students, researchers and application specialists as well.

• I INTRODUCTION TO NEURAL NETWORKS; II ADVANCED NEURAL NETWORKS; III INFORMATION THEORY AND NEURAL NETWORKS; IV MACROSCOPIC ANALYSIS OF DYNAMICS; V EQUILIBRIUM STATISTICAL MECHANICS OF NEURAL NETWORKS; APPENDICES; REFERENCES

The book provides an excellent class-tested material for graduate courses in artificial neural networks. It is completely self-contained and includes also thorough introduction to the discussed discipline-specific areas of mathematics...Therefore, this book represents a good reference source of applicable ideas for a wide audience including students, researchers and application specialists as well.

• I INTRODUCTION TO NEURAL NETWORKS; II ADVANCED NEURAL NETWORKS; III INFORMATION THEORY AND NEURAL NETWORKS; IV MACROSCOPIC ANALYSIS OF DYNAMICS; V EQUILIBRIUM STATISTICAL MECHANICS OF NEURAL NETWORKS; APPENDICES; REFERENCES