Blind Signal Separation and Recovery in Dynamic Environments

This work bridges the gap between activities motivated from statistical signal processing, neuromorphic systems, and microelectronic implementation techniques for blind separation and recovery of mixed signals. The composition adopts both discrete-time and continuous-time formulations with a view towards implementations in the digital as well as the analog domains of microelectronic circuits. This paper focuses on the development and formulation of dynamic architectures with adaptive update laws for multi-source blind signal separation/recovery.