InSAR Filtering Code Implementation
Excellent InSAR filtering solution with beginner-friendly code structure and comprehensive documentation
Explore MATLAB source code curated for "滤波" with clean implementations, documentation, and examples.
Excellent InSAR filtering solution with beginner-friendly code structure and comprehensive documentation
Implementation of a half-band filter with 2x interpolation for efficient signal filtering and rate conversion
Using Wiener filter algorithm for denoising signal processing with code implementation approaches
Implementation of radar time delay calculation and positioning using wavelet-based filtering and local correlation algorithms with MATLAB/Python code integration.
This MATLAB-based speech recognition program implements voice detection and filtering techniques, featuring comprehensive audio signal processing capabilities for accurate speech analysis.
Record your own voice signal and sample the recorded signal; plot the time-domain waveform and spectrogram of the sampled voice signal; design a filter using the window function method and bilinear transform based on specified filter performance requirements, and plot the filter's frequency response; apply the designed filter to process the acquired signal, plot the filtered signal's time-domain waveform and spectrum, compare pre- and post-filtering signals, and analyze signal changes; playback the voice signal; finally, design a signal processing system interface with integrated functions.
Key programs for electromagnetic field polarization filtering accompanied by a classic Kalman filter framework template designed for ready-to-use implementation with plug-and-play adaptability
Implementation of LS channel estimation using comb-type pilot sequences with linear interpolation and time-domain interpolation filtering for complete channel response acquisition
This application enables clear visualization of grayscale histograms for images while providing smoothing and filtering operations, facilitating programmers' image analysis through histogram equalization and spatial filtering implementations.
Separately filtering Y, U, and V component channels in YUV video using different filtering techniques