Explore MATLAB source code curated for "频域" with clean implementations, documentation, and examples.
Comprehensive Signal Feature Extraction Using 16 Statistical Metrics: Mean, Standard Deviation, Variance, Skewness, Kurtosis, Peak-to-Peak, Peak Value, RMS Amplitude, Average Amplitude, Root Amplitude, Waveform Factor, and Crest Factor with Code Implementation Insights
2. Image Enhancement: Image enhancement, also known as image sharpening, aims to strengthen detail information such as contour edges in images. Similar to image smoothing, image enhancement can be performed in both spatial and frequency domains. For spatial domain sharpening: subtracting the original image from a processed version yields the sharpened image g(i,j), i.e., g(i,j) = f(i,j) - α[f(i+1,j) + f(i-1,j) + f(i,j+1) + f(i,j-1) - 4f(i,j)] = f(i,j) + 4α[f(i,j) - avg]. Here α is an adjustable factor controlling sharpening intensity, where 1/4 represents the average gray value of the 4 neighboring points around the sharpened pixel.
One of the frequency-domain modal parameter identification methods enables vibration signal analysis to extract structural natural frequencies, damping ratios, and mode shapes. This well-established method features complete implementation code with robust algorithmic approaches for accurate parameter estimation.
Explores an iterative blind restoration algorithm leveraging both spatial and frequency domains, a research hotspot in image blind restoration with demonstrated high effectiveness through practical implementation and experimental validation.
Simulation of time-domain, frequency-domain, and ambiguity functions for various radar pulse compression signals with code implementation insights
A frequency-domain modal parameter identification method for vibration signal analysis and processing, capable of extracting structural natural frequencies, damping ratios, and mode shape coefficients. The method is highly effective, with complete program implementation featuring signal preprocessing, frequency response function estimation, and curve fitting algorithms.
Frequency domain image enhancement with multiple working examples, successfully debugged and verified in MATLAB environment. Includes practical code implementations demonstrating various enhancement techniques.
Voice processing software with GUI interface, original implementation featuring time-domain and frequency-domain analysis, waveform visualization, window functions, and recording capabilities.
Code implementation for spotlight SAR system simulation and reconstruction, featuring frequency domain variations and signal processing algorithms.
MATLAB Program for Time Domain, Frequency Domain, and Time-Frequency Domain Feature Extraction of Tool Fault Signals in Online Monitoring - Implementing signal processing algorithms for tool condition analysis using statistical features, FFT analysis, and wavelet transform techniques