In New Directions in Statistical Signal Processing, leading researchers from both signal processing and presenting new work neural computation that aims to enhance the interaction between the two disciplines. 14 chapters of this book, almost evenly divided between signal processing and neural computation, begin with the brain and switched to communications, signal processing, and learning systems. They examine topics such as how computational models help us understand brain information processing, how intelligent machine that could solve the "cocktail party problem" with "active audition" in a noisy environment, graphical and network structure approach to modeling, uncertainty in communications networks, geometry approach to blind signal processing, learning algorithm, game-theory, operator models and observed (OOMs) as an alternative to hidden Markov models (HMMs).