Advanced Signal Processing and Digital Noise Reduction

Introduction to Signal Processing and Noise Reduction Stochastic Processes and Statistical Characterization of Signals Signal Transforms Bayesian Probabilistic Estimation Theory Wiener Filters and Kalman Filters Linear Prediction Models Sample-Adaptive Least Squared Error Filters Power Spectrum Estimation Finite-State Statistical Models for Non-stationary Stochastic Processes Interpolation of a Sequence of Samples Modelling, Detection and Removal of Impulsive Noise Spectral Subtraction Removal of Transient Noise Pulses Echo Cancellation and Multi-Input Adaptive Noise Reduction Adaptive Notch Filters Channel Equalization Noise Compensation for Speech Recognition in Adverse Environments.