Looking for inspiring MATLAB projects to sharpen your skills or impress in your next assignment? At MATLABSolutions.com , we’ve curated the top 12 MATLAB projects that showcase the power of MATLAB in signal processing, image analysis, machine learning, and more. These hands-on examples, complete with code and explanations, are perfect for beginners and advanced users alike. Dive in and explore the best MATLAB projects to elevate your expertise! Signal Smoothing with Moving Average Filter Master signal processing by smoothing noisy data using MATLAB’s movmean function. This project cleans a synthetic sine wave, teaching you noise reduction basics. Ideal for audio or sensor data analysis. Get the code at MATLABSolutions Projects Image Edge Detection Using Canny Filter Explore image processing with MATLAB’s Canny edge detection algorithm. This project highlights edges in any photo, perfect for computer vision applications. Download the script and try it on your own images! Bitcoin Price ...
I am trying to find the method of locating the gaussian peaks from the photon count data. x axis is the number of photons for each spot and y axis is the counted spots.
I used findpeaks function to find peaks. The solid line is created by sgolayfilt.
hgcs = sgolayfilt(hgc, 10, 41); plot(hgc); hold on;plot(hgcs) findpeaks(hgc, 'MinPeakDistance', 20)
The peaks that I want to recover are located about 40, 80, 120, and 160.
Question1: Are there any functions or algorithms that can determine the number of peaks and the locations?
Question2: After 160, there are small features. Some of them may be still peaks following the first four peaks. At least, we know that the locations of peaks are quasi-periodic. Could we also find more peaks?
ANSWER
Matlabsolutions.com provide latest MatLab Homework Help,MatLab Assignment Help for students, engineers and researchers in Multiple Branches like ECE, EEE, CSE, Mechanical, Civil with 100% output.Matlab Code for B.E, B.Tech,M.E,M.Tech, Ph.D. Scholars with 100% privacy guaranteed. Get MATLAB projects with source code for your learning and research.
I gave up on estimating the width parameter, and just went for the amplitude and location with a uniform width.Try This: D = load('hgc.mat');
hgc = D.hgc;
x = linspace(0, numel(hgc), numel(hgc));
hgcs = sgolayfilt(hgc, 10, 41);
figure
plot(x,hgc)
hold on
plot(x,hgcs)
hold off
grid
[pks,locs,w] = findpeaks(hgc, 'MinPeakDistance', 20, 'MinPeakProminence',5);
gausfcn = @(b,x) b(1).*exp(-(x-b(2)).^2 * 0.05);
for k = 1:numel(locs)
SEE COMPLETE ANSWER CLICK THE LINK
Matlabsolutions.com provide latest MatLab Homework Help,MatLab Assignment Help for students, engineers and researchers in Multiple Branches like ECE, EEE, CSE, Mechanical, Civil with 100% output.Matlab Code for B.E, B.Tech,M.E,M.Tech, Ph.D. Scholars with 100% privacy guaranteed. Get MATLAB projects with source code for your learning and research.
I gave up on estimating the width parameter, and just went for the amplitude and location with a uniform width.
Try This:
D = load('hgc.mat'); hgc = D.hgc; x = linspace(0, numel(hgc), numel(hgc)); hgcs = sgolayfilt(hgc, 10, 41); figure plot(x,hgc) hold on plot(x,hgcs) hold off grid [pks,locs,w] = findpeaks(hgc, 'MinPeakDistance', 20, 'MinPeakProminence',5); gausfcn = @(b,x) b(1).*exp(-(x-b(2)).^2 * 0.05); for k = 1:numel(locs)
SEE COMPLETE ANSWER CLICK THE LINK
Comments
Post a Comment