I have a spectrum recovery algorithm based on OMP. I want to use it for wireless sensors to optimize their data procession and data transfer as they generate loads of sensed parametric data.
My algorithm is in matlab and I need to reduce its execution time to make it fast enough to make my sensor nodes able to learn faster and adapt accordingly.
Dear Charushila,
welcome,
There are tow levels of optimizations:
The algorithmic optimization
In such algorithmic optimization you construct your logical and mathematical solution of the problem to reduce the mathematical operations required to get the results especially the multiplications and divisions.
The code building such that you minimize the redundant calcualtions.
If you have enough memory you can trade off against the processing. Memory accessing time may be smaller than calculating of a specific parameter.
You have to analyse the program to optimize it.
There is methods and tips published in the literature that you can apply for the reduction of the execution time.
You need only to use the key word: matlab code optimization
Best wishes
Dear Charushila,
welcome,
There are tow levels of optimizations:
The algorithmic optimization
In such algorithmic optimization you construct your logical and mathematical solution of the problem to reduce the mathematical operations required to get the results especially the multiplications and divisions.
The code building such that you minimize the redundant calcualtions.
If you have enough memory you can trade off against the processing. Memory accessing time may be smaller than calculating of a specific parameter.
You have to analyse the program to optimize it.
There is methods and tips published in the literature that you can apply for the reduction of the execution time.
You need only to use the key word: matlab code optimization
Best wishes
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