ECG Signal Feature Extraction and Data Processing
ECG signal eigenvalue analysis, power spectrum computation, filtering techniques, and related data processing methods for cardiac health assessment
Generating Pulsating Wind Speed Time History Data Using Power Spectrum Method with AR Linear Filtering Technique
This methodology employs power spectrum approach combined with AR linear filtering to generate pulsating wind speed time histories, suitable for calculating structural wind loads. The implementation involves spectral decomposition and autoregressive modeling to simulate realistic wind fluctuations.
Generating RF Noise Interference Signals
Generate RF noise interference signals and visualize their waveform and power spectral density
Displacement Curve Analysis for a Differential Equation Example
Implementation of displacement curve analysis, phase diagram plotting, power spectrum computation, Poincaré section visualization, and motion animation simulation for a differential equation system modeling spring-damper dynamics
MATLAB Code Implementation for Power Spectral Density Calculation
A comprehensive program for computing power spectrum density from time-domain signals, featuring efficient Fast Fourier Transform (FFT) algorithms and spectral estimation techniques.
Analyzing Speech Signal Processing Using MATLAB Tools
This analysis explores key aspects of speech signal processing using MATLAB, including short-time energy computation, endpoint detection algorithms, and power spectrum analysis with short-time Fourier transform characteristics. The study provides practical code implementation approaches for each technique.
MATLAB Simulation of Power Spectrum Analysis
MATLAB simulation code for power spectrum analysis, complete with implementation examples and parameter customization guidance to facilitate learning and application in signal processing projects.
Simulink Simulation of MSK and GMSK with Code Implementation Features
Simulink simulation of MSK and GMSK modulation techniques featuring eye pattern analysis, power spectral density evaluation, and signal quality assessment methods
Power Spectrum Estimation of Sequences Using the Periodogram Method
Estimating the power spectrum of sequences using the periodogram method with a Hamming data window. The scenario involves resolving three sinusoidal signals of different frequencies embedded in white noise, where phases are independent random variables uniformly distributed over 2π, and amplitude corresponds to unit white noise. A collection of 50 sample sequences, each of length N=512, is generated for analysis.
MATLAB Code Implementation for Generating Gaussian White Noise with Signal Analysis
Generating Gaussian white noise using MATLAB with visualization of time-domain waveform, autocorrelation function, and power spectrum density through complete signal processing workflow.