Time-Frequency Analysis Using the Ambiguity Function Method
Implementation of time-frequency analysis using the ambiguity function method - a robust program originally developed for academic research and paper writing purposes.
Gabor Transform for Time-Frequency Analysis
Gabor transform for time-frequency analysis, which generates time-frequency analysis spectrograms for signal processing
Computation of Instantaneous Frequency Functions
Calculating instantaneous frequency functions, primarily used in time-frequency analysis with MATLAB implementation
MATLAB and Time-Frequency Analysis Toolbox
This repository contains MATLAB source code from our time-frequency analysis toolbox, specifically designed for processing EEG spectrograms and raw EEG waveform data with comprehensive signal processing capabilities.
Designing Optimal Filters for Speech Denoising
• Plot the noisy speech signal in both time-domain and frequency-domain representations • Perform time-frequency analysis of noise-corrupted speech signals • Design and implement appropriate digital filters for speech denoising using signal processing algorithms • Apply filter design techniques to remove noise components while preserving speech characteristics • Plot the cleaned signal in both time-domain and frequency-domain for performance validation • Conduct time-frequency analysis of processed signals to evaluate denoising effectiveness • Explore advanced audio processing applications including reverberation systems
Wigner-Ville Distribution: A MATLAB-Based Time-Frequency Analysis Method
Implementation of Wigner-Ville Distribution using MATLAB for advanced time-frequency signal analysis with code implementation details
Meteorological Radar Echoes with Rayleigh Distribution
Analysis of Rayleigh-distributed weather radar echoes, including time-frequency analysis, power spectral density, and spectral distribution characteristics with implementation approaches.
Time-Frequency Analysis of Noisy Speech Signals with Denoising and Reverberation Processing
1. Perform time-frequency analysis on noisy speech signals using spectrogram and periodogram methods 2. Design appropriate digital filters (FIR/IIR) for denoising through frequency response analysis 3. Conduct post-denoising time-frequency analysis to evaluate performance metrics 4. Implement a reverberation effect using four comb filters and two all-pass filters with equalizer integration for echo generation
Time-Frequency Analysis of Transient Signals Using STFT, Wavelet Transform, and EMD
Comparative time-frequency analysis of transient signals using Short-Time Fourier Transform (STFT), Wavelet Transform, and Empirical Mode Decomposition (EMD) with code implementation insights
Time-Frequency Analysis of Speech Signals
Time-frequency analysis of speech signals is a crucial area of research. Speech recognition technology, as one of the key technologies driving the development of intelligent and automated information societies, holds significant research importance and practical value. Through nearly five decades of intensive exploration and research, speech recognition technology has achieved remarkable progress, with some mature techniques already being applied in daily life. However, overall, speech recognition still presents considerable challenges in both research and practical applications. This article provides a comprehensive overview of speech recognition technology, covering key techniques, specific applications, and current difficulties, and includes MATLAB-based simulation analysis of individual speech samples. Code implementations focus on signal processing techniques such as Short-Time Fourier Transform (STFT) and wavelet analysis for feature extraction.