CMM344 Digital Signal Analysis and Processing
Digital Signal Analysis and Processing notes
10 chapter notes, in syllabus order. Each starts with the key points.
Unit 1
Discrete-Time Signals & Systems: Classification, Operations & PropertiesUnit 1 of Digital Signal Analysis and Processing covers discrete-time signals (classification, operations, properties) and systems (causality, linearity, time-invariance, stability), with visual tools like signal plots, system block diagrams, and real-world DSP applications in Nepalese tech.11 min readUnit 2
LTI Systems: Properties, Convolution, Stability & CausalityUnit 2 of Digital Signal Analysis and Processing explores Linear Time-Invariant (LTI) systems, covering their defining properties, impulse response, convolution, stability, causality, and real-world applications in signal processing pipelines like audio compression (WhatsApp voice notes) and financial forecasting (NEPS9 min readUnit 3
Z-Transform: Definition, Properties, Inversion, ApplicationsUnit 3 of Digital Signal Analysis and Processing covers the Z-transform, its properties, inverse transform, region of convergence (ROC), and applications in solving linear difference equations and analyzing discrete-time systems.18 min readUnit 4
Frequency Analysis: Fourier, Periodicity, Power SpectrumUnit 4 of Digital Signal Analysis and Processing covers how to decompose signals into their frequency components using Fourier analysis, periodicity tests, power spectral density, and windowing techniques—essential for designing filters, compressing audio, and analyzing real-world signals like speech or ECG.10 min readUnit 5
Discrete Fourier Transform: DFT, Properties, ApplicationsUnit 5 of Digital Signal Analysis and Processing covers the Discrete Fourier Transform (DFT), its mathematical formulation, key properties, computational efficiency, and real-world applications in signal processing, including spectral analysis, filtering, and compression.12 min readUnit 6
Fast Fourier Transform: FFT Algorithms, Properties & ApplicationsUnit 6 of Digital Signal Analysis and Processing covers the Fast Fourier Transform (FFT), its recursive and iterative algorithms (Radix-2, Radix-4, Split-Radix), computational efficiency, and real-world applications in signal processing, including spectral analysis, filter design, and compression.7 min readUnit 7
Digital Filter Structures: Types, Designs & ImplementationsUnit 7 of Digital Signal Analysis and Processing explores the architecture, classification, and implementation of digital filters—covering FIR/IIR structures, direct/transpose forms, lattice filters, and hardware considerations like quantization effects and DSP processor constraints.15 min readUnit 8
IIR Filter Design: Butterworth, Chebyshev, Elliptic, and State-Variable MethodsUnit 8 of Digital Signal Analysis and Processing covers IIR filter design techniques, including Butterworth, Chebyshev, and Elliptic filters, their frequency responses, pole-zero plots, and state-variable implementation. It also explains bilinear transformation, filter stability, and real-world applications in audio pr9 min readUnit 9
FIR Filter Design: Types, Methods & ApplicationsUnit 9 of Digital Signal Analysis and Processing covers Finite Impulse Response (FIR) filter design, including windowing methods, frequency sampling, and equiripple techniques. Learn how to design FIR filters for lowpass, highpass, bandpass, and bandstop applications, compare them with IIR filters, and apply them in re17 min readUnit 10
DSP Applications: Filters, Speech, Audio, Video & Real-Time SystemsUnit 10 of Digital Signal Analysis and Processing explores how DSP techniques are applied in real-world systems, covering audio processing, speech coding, image/video compression, biomedical signal analysis, and real-time embedded systems. This note includes industry examples, design trade-offs, and hands-on case studi14 min read