DSP System

Digital signal processing (DSP) is the numerical manipulation of signals, usually with the intention to measure, filter, produce or compress continuous analog signals. Signal processing is essential for a wide range of applications, from data science to real-time embedded systems.   MATLAB and Simulink products make it easy to use signal processing techniques to explore and analyze time-series data, and they provide a unified workflow for the development of embedded systems and streaming applications.

Following is the list of topics under DSP System which is prepared after detailed analysis of courses taught in multiple universities across the globe:

  • Adaptive Filters
  • Analyze the stability of systems
  • Applications of DSP
  • Code Generation
  • Data and Signal Management
  • Digital Filter Structures
  • Digital Signal Processing
  • Discrete-Time Fourier Analysis
  • Discrete-Time Signals and Systems
  • Fast Fourier transform
  • FDATool: A Filter Design and Analysis GUI
  • Filter Analysis, Design, and Implementation
  • Filter Design Using MatLab
  • Filterbuilder GUI
  • find the system transfer function
  • finite impulse response digital filters
  • Finite impulse response system
  • Fixed-Point Design
  • Fourier and Z-transforms
  • Input, Output, and Display
  • Introduction to Digital Systems
  • Introduction to MatLab and SimuLink
  • Lowpass FIR Filters
  • Mathematics using Matlab
  • Multirate and Multistage Filters
  • New System Objects
  • Optimal Equal- Ripple Design Techniques
  • Sampling/reconstruction of continuous time signals
  • The Discrete Fourier Transform
  • The Fast Fourier Transform
  • The Z-Transform
  • Transforms, Estimation, and Spectral Analysi
  • Two-dimensional signals and introductory image