**/**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