Linear Array Pattern Plotting with Parameter Configuration
Generate linear array radiation patterns with adjustable element count and windowing functions through a comprehensive GUI interface
Speech Frame Processing: Framing, Windowing, Denoising, and Endpoint Detection
A self-developed program implementing speech frame segmentation, windowing, noise reduction, and endpoint detection algorithms, successfully debugged and optimized for speech signal processing
MATLAB Implementation of Speech Recognition Preprocessing
MATLAB implementation for speech recognition preprocessing including endpoint detection, pre-emphasis, and windowing techniques with algorithmic explanations
Speech Signal Analysis Using Short-Time Fourier Transform
This program implements speech signal analysis through Short-Time Fourier Transform, including windowing and framing processing with detailed code implementation for spectral feature extraction
Spectral Subtraction-Based Voice Activity Detection
Voice activity detection using spectral subtraction method, incorporating techniques such as speech enhancement, noise reduction, spectral subtraction, windowing, and endpoint detection algorithms with code implementation details
Speech Frame Analysis: Windowing, Short-Time Energy, Zero-Crossing Rate, and Endpoint Detection
MATLAB implementation for plotting Hanning, Hamming, and Blackman windows in a single figure, with practical applications in speech frame segmentation, windowing, short-time energy calculation, zero-crossing rate analysis, and endpoint detection algorithms.
Pre-processing Steps for Speech Signal Processing
The pre-processing stage of speech signal processing, including pre-emphasis, framing, and windowing operations, serves as an excellent introductory reference program for speech signal programming beginners.
MATLAB Source Code for OFDM Windowing Technique
MATLAB source code implementing OFDM windowing method specifically designed to reduce Peak-to-Average Power Ratio (PAPR) in orthogonal frequency division multiplexing systems
Spectral Estimation Analysis with Different Segment Lengths
Investigation of three different L values: L=256 (3 data segments), L=128 (7 data segments), and L=64 (15 data segments). The corresponding spectral estimation plots demonstrate that windowing effectively reduces false spectral peaks but further smoothes actual peaks. For L=64, the spectral line at ω=0.8π is clearly identifiable, but adjacent peaks remain difficult to distinguish. L=128 provides optimal balance between resolution and detection capability, while L=256 yields superior results with clear identification of three spectral lines and their amplitude relationships. Beyond Welch's method, alternative approaches like Bartlett's method can be implemented using periodogram averaging for power spectrum estimation.
Fundamental MATLAB Processing Programs for Speech Signal Processing
Essential MATLAB processing programs for speech signal analysis, including waveform reading, voiced/unvoiced detection, windowing, zero-crossing rate calculation, short-time energy analysis, and maximum pitch detection. The package concludes with a demonstration test showing practical implementation.