Signal Spectrum Analysis Using FFT
Performing signal spectrum analysis using FFT (Fast Fourier Transform) in digital signal processing applications including implementation approaches and key algorithmic considerations.
MATLAB Implementation of OFDM Simulation with Complete Source Code
OFDM simulation program featuring parameter configuration, FFT/IFFT operations, modulation/demodulation algorithms with full source code - highly practical for wireless communication research!
Deepening Understanding of Fast Fourier Transform (FFT) Fundamentals
1. Deepen comprehension of Fast Fourier Transform (FFT) fundamental principles through practical experiments. 2. Explore the relationship between FFT point count and spectral resolution, and analyze connections between zero-padded sequence FFT and original sequence FFT implementations. Discrete Fourier Transform (DFT) and convolution represent two fundamental operations in signal processing, involving extensive applications in signal and system analysis/synthesis. These operations are interconnected: convolution can be implemented via DFT, while numerous algorithms including correlation, filtering, and spectral estimation can be DFT-based. Conversely, DFT can also be realized through convolution operations, demonstrating their mathematical equivalence in digital signal processing.
Spectral Analysis Using Classic Periodogram (FFT) on Data in MATLAB
Performing frequency domain analysis on a given data set in MATLAB using the classic periodogram method with Fast Fourier Transform (FFT) implementation
Generate Simulated BPSK Signals with Spectrum Analysis
Using MATLAB to generate simulated BPSK signals and performing spectral analysis through FFT implementation, including parameter configuration and frequency domain characterization.
Fast Fourier Transform FFT Universal Implementation
This universal MATLAB source program demonstrates Fast Fourier Transform (FFT) algorithm implementation. Since MATLAB's built-in fft function doesn't reveal source code, this custom implementation provides educational value for beginners learning signal processing algorithms and MATLAB programming techniques.
Performance Evaluation of CA-CFAR Algorithm on Sinusoidal Beat FFT with Controllable SNR
Testing the CA-CFAR algorithm on FFT-processed sinusoidal beat signals with programmable signal-to-noise ratio control
FFT-Based 3D Gaussian Rough Surface Generation
Generation of 3D Gaussian rough surfaces using Fast Fourier Transform (FFT) methods, enabling rapid simulation for advanced research applications with efficient computational implementation
Envelope Demodulation Algorithm
This algorithm implements two distinct methods for envelope demodulation: the first approach applies Hilbert transform followed by FFT analysis, while the second method squares the signal before passing it through a low-pass filter (LPF) and performing FFT.
Fundamental Signal Processing Algorithms for SAR Radar
This collection contains 16 files implementing core SAR radar signal processing algorithms including FFT, range compression (CRANGE), and other essential functions. These implementations provide beginners with practical understanding of radar signal processing workflows, target information extraction methods, and algorithm application scenarios.