tsaith.github.io

TH's Notes

Recent Posts all posts. Detect peaks with CFAR algorithm. Tue 15 March 2016. Derivation of the MFSK algorithm used in automotive radar systems. Sat 05 March 2016. Time-frequency analysis with Short-time Fourier transform. Mon 22 February 2016. Simulating FM waves used in automotive radars. Sun 21 February 2016. Derive and implement multiclass SVM layer. Sun 14 February 2016. Derive and implement softmax layer. Sun 14 February 2016. Implement stacked multilayer perceptron for digit recognition.

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Recent Posts all posts. Detect peaks with CFAR algorithm. Tue 15 March 2016. Derivation of the MFSK algorithm used in automotive radar systems. Sat 05 March 2016. Time-frequency analysis with Short-time Fourier transform. Mon 22 February 2016. Simulating FM waves used in automotive radars. Sun 21 February 2016. Derive and implement multiclass SVM layer. Sun 14 February 2016. Derive and implement softmax layer. Sun 14 February 2016. Implement stacked multilayer perceptron for digit recognition.

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TH's Notes | tsaith.github.io Reviews

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Recent Posts all posts. Detect peaks with CFAR algorithm. Tue 15 March 2016. Derivation of the MFSK algorithm used in automotive radar systems. Sat 05 March 2016. Time-frequency analysis with Short-time Fourier transform. Mon 22 February 2016. Simulating FM waves used in automotive radars. Sun 21 February 2016. Derive and implement multiclass SVM layer. Sun 14 February 2016. Derive and implement softmax layer. Sun 14 February 2016. Implement stacked multilayer perceptron for digit recognition.

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tsaith.github.io

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Derivation of the MFSK algorithm used in automotive radar systems · TH's Notes

http://tsaith.github.io/derivation-of-the-mfsk-algorithm-used-in-automotive-radar-systems.html

Derivation of the MFSK algorithm used in automotive radar systems. This article describes the derivation of MFSK algorithm, which provides the possibility to detect the range and velocity of multiple targets in automotive radar systems. Considering the waveform of MFSK as depicted,. This picture is copied from Matlab doc]. Here, there are (2N ). Steps in the waveform. (f {sweep} = (N-1) f {step} ). Is the frequency sweep range. (f {step} ). Is the chirp time duration. (T {step} ). Define ( bar{f b} = f b...

2

Implement softmax regression for digit recognition · TH's Notes

http://tsaith.github.io/implement-softmax-regression-for-digit-recognition.html

Implement softmax regression for digit recognition. This post will demonstrate how to implement softmax regression. The detailed derivations of algorithm can be found from this script. Set the weight decay / numerical parameters. Check if the gradients of the loss function are correct. Estimate the accuracy of predictions. Dnn play.classifiers.softmax. Dnn play.utils.data utils. Dnn play.utils.visualize utils. Set default size of plots. X train shape =. Y train shape =. X val shape =. Y val shape =.

3

Time-frequency analysis with Short-time Fourier transform · TH's Notes

http://tsaith.github.io/time-frequency-analysis-with-short-time-fourier-transform.html

Time-frequency analysis with Short-time Fourier transform. The essential idea of STFT. Is to perform the Fourier transform on each shorter time interval of the total time series to find out the frequency spectrum at each time point. In the following example, we will show how to use STFT to perform time-frequency analysis on signals. Set default size of plots. The autoreload extension is already loaded. To reload it, use: %reload ext autoreload. Define functions ¶. Frame size: Frame size. Feb 22, 2016.

4

Implement multilayer perceptron for digit recognition · TH's Notes

http://tsaith.github.io/implement-multilayer-perceptron-for-digit-recognition.html

Implement multilayer perceptron for digit recognition. This post will demonstrate how to implement multilayer perceptron for digit recognition. The detailed derivations of algorithm can be found from this script. Set the weight decay / numerical parameters. Check if the gradients of the loss function are correct. Estimate the accuracy of predictions. Dnn play.classifiers.mlp. Dnn play.utils.data utils. Dnn play.utils.visualize utils. Set default size of plots. X train shape =. Y train shape =.

5

Detect peaks with CFAR algorithm · TH's Notes

http://tsaith.github.io/detect-peaks-with-cfar-algorithm.html

Detect peaks with CFAR algorithm. In this post, we will introduce the cell-averaging CFAR. Constant False Alarm) algorithm to detect peaks of signals. This picture is copied from Matlab doc]. Assuming (x j ). Is the value of the (j ). Th test cell, we declare that the test cell has a peak if (x j ). Is greater than the value of adjacent cells and (x j T ). Where T is the threshold. T = alpha P n $. Alpha = N (P {fa} {-1/N} - 1) $. P n = frac{1}{N} sum {m=1} {N} x m $. Where ( alpha ). Comments powered by...

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TH's Notes

Recent Posts all posts. Detect peaks with CFAR algorithm. Tue 15 March 2016. Derivation of the MFSK algorithm used in automotive radar systems. Sat 05 March 2016. Time-frequency analysis with Short-time Fourier transform. Mon 22 February 2016. Simulating FM waves used in automotive radars. Sun 21 February 2016. Derive and implement multiclass SVM layer. Sun 14 February 2016. Derive and implement softmax layer. Sun 14 February 2016. Implement stacked multilayer perceptron for digit recognition.

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