DEMO MPE ( MULTICOMPONENT PARAMETER ESTIMATORS ) IMPLEMENTATIONS

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This document presents the implementations and comparative analysis of multi-component parameter estimators by Cesar Aceros-Moreno, PhD student under Prof. Domingo Rodriguez at the University of Puerto Rico, Mayagüez Campus. The study includes both uni-processor and multi-processor implementations, focusing on Fast Fourier Transform (FFT) comparisons. It evaluates parameter estimation results under varying signal-to-noise ratios (SNR), detailing successful and unsuccessful estimations, and presents an implementation of the ambiguity function for different signals, including pulse and chirp signals.

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demo mpe multicomponent parameter estimators implementations

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May 15, 2026

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1 parameter estimation 2 signal processing 3 multiprocessor implementations 4 fast fourier transform 5 ambiguity function 6 noise analysis 7 uniprocessor implementations 8 snr comparisons text

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DEMO MPE ( MULTICOMPONENT PARAMETER ESTIMATORS ) IMPLEMENTATIONS

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DEMOMPE ( MULTICOMPONENT PARAMETER ESTIMATORS ) IMPLEMENTATIONS By: Cesar Aceros-Moreno, PhD Student Advisor: Prof. Domingo Rodriguez Automated Information Processing Laboratory (AIP) University of Puerto Rico, Mayagüez Campus (UPRM) May 2007
Uni-processor Implementations FFT Comparison Single Processor Implementation Results DCFT/AF Comparison
Multi-processor Implementations Multi-processor Implementation Results Comparison for DCFT Multi-processor
Multicomponent Parameter Estimation Unsuccessful Parameter Estimation (3 dB SNR) Successful Parameter Estimation (6 dB SNR)
Ambiguity Function Implementation Ambiguity Function of a Pulse Ambiguity Function of a Chirp Signal