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antenna-arrays

Produces radiation pattern for Broadside, Endfire, Binomial, and Dolph - Chebyshev antenna arrays

antenna-arrays-in-3d

Produces radiation pattern for Broadside, Endfire, and Binomial antenna arrays in 3 dimensions

autotunepidcontroller

basic-phasor-plot

Drawing Basic phasor diagram This code shows how to draw a basic phasor and use plot windows

birthday-cake

This code bakes a birthday cake for someone special to whom you wanna surprise on his/her birthday

error-correcting-algorithms

It consists of Viterbi, Trellis, and Cyclic codec

ics-43434-breakout-board

Sample code for the ICS-43434 breakout board and the ESP32

intelligent-ebook

This is C code for my ARM7-core based Intelligent ebook.

mywhatsappstickerapp

slsbdu-system-identification

t81_558_deep_learning

Washington University (in St. Louis) Course T81-558: Applications of Deep Neural Networks

ufldl_cnn

ufldl_lineardecoders

An autoencoder with a sigmoid (or tanh) hidden layer and a linear output layer is Linear Decoders. If one uses PCA whitening, the input is no longer constrained to [0,1], then you go for Linear Decoders

ufldl_pca-2d

Implementation of PCA, PCA whitening and ZCA whitening in 2D

ufldl_pca-and-zca-whitening

Implementation of PCA and ZCA whitening, and applying them to image patches taken from natural images.

ufldl_selftaughtlearning

In Self-taught learning and Unsupervised feature learning, we will give our algorithms a large amount of unlabeled data with which to learn a good feature representation of the input.

ufldl_softmaxregression

This model generalizes logistic regression to classification problems where the class label y can take on more than two possible values.

ufldl_sparseautoencoder

An unsupervised learning algorithm that applies back propagation, setting the target values to be equal to the inputs. Also, we impose a sparsity constraint on the hidden units, then the autoencoder will still discover interesting structure in the data, even if the number of hidden units is large.

ufldl_stackedae

A stacked autoencoder is a neural network consisting of multiple layers of sparse autoencoders in which the outputs of each layer is wired to the inputs of the successive layer.