Digital And Kalman Filtering: An Introduction T... -

It covers the two primary classes of digital filters: Finite Impulse Response (FIR) filters, which are always stable and can have linear phase, and Infinite Impulse Response (IIR) filters, which are more computationally efficient but involve feedback loops.

The second half addresses the challenge of extracting a "true" signal from data corrupted by noise—a central problem in communications, radar, and control systems. Digital and Kalman Filtering: An Introduction t...

The first half of the text focuses on the design and analysis of discrete-time systems. Key topics include: It covers the two primary classes of digital

Practical methods for calculating how filters attenuate or boost specific frequency ranges, including graphical computation methods. Part 2: Optimum Linear Estimation Key topics include: Practical methods for calculating how

The mathematical framework for analyzing these systems, using difference equations to represent how the current output depends on present and past inputs (and past outputs for IIR systems).

by S.M. Bozic is a foundational text that bridges the gap between classical digital signal processing and advanced estimation theory.