by S.M. Bozic is a foundational text that bridges the gap between classical digital signal processing and advanced estimation theory.
The book is structured in two halves to guide students and engineers from basic filter design to the practical application of the Kalman filter in noisy environments. Part 1: Digital Filtering Fundamentals 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. Part 1: Digital Filtering Fundamentals It covers the
The first half of the text focuses on the design and analysis of discrete-time systems. Key topics include: Part 2: Optimum Linear Estimation The second half
Practical methods for calculating how filters attenuate or boost specific frequency ranges, including graphical computation methods. Part 2: Optimum Linear Estimation
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.