Current Practices and Future Research Directions in Adaptive Signal Processing
While the theory and design of linear adaptive filters based on FIR filter structures is well developed and widely applied in practice, the same situation is not true for linear IIR or for nonlinear adaptive filters in general. The latter situation exists because both linear IIR structures and nonlinear structures sometimes produce multi-modal error surfaces on which stochastic gradient optimization strategies fail to reach the global minimum. This seminar begins with a concise review of state-of-the-art techniques in linear adaptive filtering, and then develops the need for nonlinear adaptive filters in applications such as nonlinear echo cancellation, nonlinear channel equalization, and acoustic channel identification. The three important evolutionary optimization algorithms will be introduced as potentially useful algorithms to deal with multimodal error surfaces. This seminar also explores how the principles of adaptive fault tolerance can be used effectively in adaptive VLSI processors that are prone to both hard and soft errors in highly integrated systems that are being scaled to smaller feature dimensions and reduced voltage thresholds.