Lecture
This lecture focuses on the Optimal Least Square Adaptive Filter, specifically the Finite Impulse Response (FIR) Filter. The instructor explains the computational burden difference between FIR and Infinite Impulse Response (IIR) filters, normal equations, and practical considerations. The lecture delves into the iterative solution of the normal equations, cost function minimization, and reducing computational complexity. Practical examples and real-time implementation challenges are discussed, emphasizing the need to optimize solutions. Various approximations and strategies to reduce computational burden are explored, including iterative solutions, merging adaptation and iteration, and replacing statistics with individual values.