Fundamental Theory - Principal Component Analysis - Engineering Assignment Help

Assignment Task :

Introduction of Project

The objectives of the project are to learn the fundamental theory on AI signal processing. For signal processing we will study on three methods, they are principal component analysis, partial least square regression and multi linear regression. After understanding the fundamental theory on AI signal processing, we will need select the best methods base on the weightage of the advantages and disadvantages, we will than apply the algorithm using MATLAB and several simulation test will be performed to better understand on the relationships between the inputs and outputs, variables and the outcome of the results. Apart from applying the algorithm, knowledge on photoacousticimaging is also required in this project. To conclude the scopes of the project, using AI algorithm to enhance a non-invasive photoacoustic sensor in terms of sensitivity and specificity which can be used to measure blood glucose.

Scope for this work, you will need to write a report base on lab experiment results. In section 2.4 & 2.5 you will need to evaluate statistically and clinically from the data obtained to validate the performance of photoacoustic sensor. You need to use ‘Linear Regression’ methods to find the correlation between glucose concertation and PA signal amplitude. Addition, use ‘Principle Component Analysis’ method to prove accordingly. All research data/information used must include IEEE referencing, figures and footnotes if necessary.

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