Superimposing Specified Noise onto Signal with Sampling Frequency Calibration

Superimposing specified noise onto a target signal using the standard NOISEX-92 noise database. The database contains various noise types including white noise, office noise, factory noise, vehicle noise, and tank noise. Signal processing applications often require noise superposition from the database, but sampling frequency mismatch between noise and clean signals necessitates calibration through resampling techniques before proper integration.

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Empirical Mode Decomposition (EMD) Implementation for Signal Analysis

Perform Empirical Mode Decomposition (EMD) on input signals, with algorithm fundamentals based on He Zhengjia's "Modern Signal Processing and Engineering Applications." Includes code implementation details for sifting process and IMF extraction.

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Radar System Signal Processing Simulation with Multi-False Target Generation and Jamming

Simulation of radar system signal processing for generating multiple false targets and implementing jamming interference

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Signal and Information Processing - MATLAB Algorithms for Array Signal Processing DOA Estimation

Signal and Information Processing - MATLAB algorithms for Direction of Arrival (DOA) estimation in array signal processing. This source code implements Root-MUSIC and MVDR algorithms with practical implementation details and performance analysis capabilities.

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MATLAB Implementation of Wavelet Analysis for Signal Processing

A comprehensive MATLAB program for wavelet analysis-based signal processing designed for fault diagnosis applications, featuring data preprocessing, multi-resolution analysis, and diagnostic visualization capabilities.

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Frequency Refinement Analysis Algorithms

Two MATLAB-developed frequency refinement analysis algorithms suitable for various signal processing applications! The programs utilize simulated data - users with MATLAB proficiency can integrate actual signals for real-world analysis.

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Signal and Information Processing - Array Signal Processing DOA Estimation

MATLAB algorithms for Direction of Arrival (DOA) estimation in array signal processing, featuring sparse decomposition algorithms for linear frequency modulation signals and Wigner-Ville distribution implementations for time-frequency analysis.

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Radar System Simulation: Techniques and Implementation

High-quality radar system simulation resources featuring downloadable programs with comprehensive code examples for studying radar signal processing techniques, including key algorithms and MATLAB/Python implementation approaches.

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Adaptive Filter File Development

This MATLAB-developed adaptive filter file serves as an excellent reference for students studying modern signal processing!

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EMD Empirical Mode Decomposition

EMD Empirical Mode Decomposition is a signal processing technique commonly used with Hilbert-Huang Transform for signal feature extraction and noise reduction applications. The implementation involves iterative sifting processes to extract Intrinsic Mode Functions (IMFs) from nonlinear and non-stationary signals.

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