New Directions in Statistical Signal Processing : From Systems to Brains.
Haykin, Simon.
New Directions in Statistical Signal Processing : From Systems to Brains. - 1st ed. - 1 online resource (525 pages) - Neural Information Processing Series . - Neural Information Processing Series .
Intro -- Series Foreword -- Preface -- 1 Modeling the Mind: From Circuits to Systems -- 2 Empirical Statistics and Stochastic Models for Visual Signals -- 3 The Machine Cocktail Party Problem -- 4 Sensor Adaptive Signal Processing of Biological Nanotubes (Ion Channels) at Macroscopic and Nano Scales -- 5 Spin Diffusion: A New Perspective in Magnetic Resonance Imaging -- 6 What Makes a Dynamical System Computationally Powerful? -- 7 A Variational Principle for Graphical Models -- 8 Modeling Large Dynamical Systems with Dynamical Consistent Neural Networks -- 9 Diversity in Communication: From Source Coding to Wireless Networks -- 10 Designing Patterns for Easy Recognition: Information Transmission with Low-Density Parity-Check Codes -- 11 Turbo Processing -- 12 Blind Signal Processing Based on Data Geometric Properties -- 13 Game-Theoretic Learning -- 14 Learning Observable Operator Models via the Efficient Sharpening Algorithm -- References -- Contributors -- Index.
Leading researchers in signal processing and neural computation present work aimed at promoting the interaction and cross-fertilization between the two fields.
9780262256315
Neural computers.
Electronic books.
QP363.3.N52 2007
006.32
New Directions in Statistical Signal Processing : From Systems to Brains. - 1st ed. - 1 online resource (525 pages) - Neural Information Processing Series . - Neural Information Processing Series .
Intro -- Series Foreword -- Preface -- 1 Modeling the Mind: From Circuits to Systems -- 2 Empirical Statistics and Stochastic Models for Visual Signals -- 3 The Machine Cocktail Party Problem -- 4 Sensor Adaptive Signal Processing of Biological Nanotubes (Ion Channels) at Macroscopic and Nano Scales -- 5 Spin Diffusion: A New Perspective in Magnetic Resonance Imaging -- 6 What Makes a Dynamical System Computationally Powerful? -- 7 A Variational Principle for Graphical Models -- 8 Modeling Large Dynamical Systems with Dynamical Consistent Neural Networks -- 9 Diversity in Communication: From Source Coding to Wireless Networks -- 10 Designing Patterns for Easy Recognition: Information Transmission with Low-Density Parity-Check Codes -- 11 Turbo Processing -- 12 Blind Signal Processing Based on Data Geometric Properties -- 13 Game-Theoretic Learning -- 14 Learning Observable Operator Models via the Efficient Sharpening Algorithm -- References -- Contributors -- Index.
Leading researchers in signal processing and neural computation present work aimed at promoting the interaction and cross-fertilization between the two fields.
9780262256315
Neural computers.
Electronic books.
QP363.3.N52 2007
006.32