The adaptive signal processing course provides introduction to relevant signal processing and basics of pattern recognition. Topics include discrete random processes, linear prediction, digital wiener filtering, digital adaptive filter structures including LMS adaptive algorithm, properties of LMS adaptive filter, normalized and finite effect and adaptive beam-forming, performance analysis of LMS algorithms, stability criteria of evaluation, and modified LMS algorithms, frequency-domain adaptive filter, least squares adaptive filters, sub-band adaptive filter, infinite impulse response filter and algorithms, lattice structure and algorithms, applications using adaptive signal processing techniques in adaptive noise cancellation in speech communication and adaptive system identification among others, practical implementations and issues in adaptive signal processing and current trends ad research in adaptive signal processing.