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3

I don't think either will increase your precision as such, although there are benefits to each approach. Using the lower 11 bits of 1.15 would provide you with 24dB of extra headroom (obviously being careful to sign extend properly). Alternatively, using the upper 11 bits could potentially lower the power in your quantisation error after 1.15 * 1.15 ...


3

there is an earlier answer regarding how to more cheaply evaluate functions like sin() and log() and such. they're approximations, but very good ones.


2

You only have 64 samples per FFT. That means your FFT bins are spaced f_sample/64; if your sample rate is 128ยท50 Hz, then your frequency resolution, without interpolation, is just 100 Hz. To achieve a frequency resolution of $0.01\,\text{Hz}=\frac{50\,\text{Hz}}{50\cdot 100} = \frac{\frac{f_{sample}}{128}}{5000}= \frac{f_{sample}}{640\cdot5000}$, you'd need ...


2

Here is some code that calculates a 1280 tap FFT based on 5 256 tap FFTs %% 1280 FFT based on five FFTs of 256 each n = 1280; % Create a piece of noise x = randn(n,1); % calculate FFT using MATLAB native fft() function. % We'll use this as a reference to prove it works fx = fft(x); % Break down into five signals of 256 points each, interleaved p = x(1:5:...


1

I think you're misunderstanding the relationship between the time and frequency domains. Each point in the output of a DFT is a function of all of the input time-domain values. There is no one-to-one mapping between input points and output points.


1

Generally, Arm Cortex-A9 type processor can be used for Audio signal processing blocks for effective results. For your case, basic arm processor type can support common floating point operations without any external floating point unit. But, in case of special floating point operations like saturation,rounding and truncation, you shall use some advanced arm ...


1

For the computation of MFCC's you usually use a DCT-II. Just implement it yourself if you can't find a proper implementation anywhere. You only have relatively few log spectral values, and probably even fewer DCT coefficients that you will use, so I hope that computational complexity will be no big issue. This document is a nice overview of all the steps ...


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