- ホーム
- > 洋書
- > 英文書
- > Science / Mathematics
Full Description
This first volume, edited and authored by world leading experts, gives a review of the principles, methods and techniques of important and emerging research topics and technologies in machine learning and advanced signal processing theory.With this reference source you will:Quickly grasp a new area of research Understand the underlying principles of a topic and its applicationAscertain how a topic relates to other areas and learn of the research issues yet to be resolved
Contents
CHAPTER 1 Introduction to Signal Processing TheoryCHAPTER 2 Continuous-Time Signals and SystemsCHAPTER 3 Discrete-Time Signals and SystemsCHAPTER 4 Random Signals and Stochastic ProcessesCHAPTER 5 Sampling and QuantizationCHAPTER 6 Digital Filter Structures and their ImplementationCHAPTER 7 Multirate Signal Processing for Software Radio ArchitecturesCHAPTER 8 Modern Transform Design for Practical Audio/Image/Video Coding ApplicationsCHAPTER 9 Discrete Multi-Scale Transforms in Signal ProcessingCHAPTER 10 Frames in Signal ProcessingCHAPTER 11 Parametric Estimation CHAPTER 12 Adaptive Filters CHAPTER 13 Introduction to Machine Learning CHAPTER 14 Learning Theory CHAPTER 15 Neural Networks CHAPTER 16 Kernel Methods and Support Vector Machines CHAPTER 17 Online Learning in Reproducing Kernel Hilbert Spaces CHAPTER 18 Introduction to Probabilistic Graphical Models CHAPTER 19 A Tutorial Introduction to Monte Carlo Methods, Markov Chain Monte Carlo and Particle FilteringCHAPTER 20 Clustering CHAPTER 21 Unsupervised Learning Algorithms and Latent Variable Models: PCA/SVD, CCA/PLS, ICA, NMF, etc.CHAPTER 22 Semi-Supervised LearningCHAPTER 23 Sparsity-Aware Learning and Compressed Sensing: An Overview CHAPTER 24 Information Based Learning CHAPTER 25 A Tutorial on Model SelectionCHAPTER 26 Music Mining
