Perceptron is one of the simplest forms of a neural network model. The following code snippet is a simple version of such a neural network using Matlab. Before using it please read some background information at wikipedia : clc; clear all; close all; % Data inputs=[1 0 0; 1 0 1;1 1 0;1 1 1]; % Desired Output desiredOutput=[1 1 1 0]; % Learning Rate learningRate=0.1; % HardLimit threshold...
Separation of Image Mixture using FastICA
Image separation of mixed and overlapped images is a frequent problem in computer vision (image processing). The following Matlab source code is a demonstration of image separation using FastICA algorithm based on kurtosis. clc;clear all;close all; original_image1=imread ('input1.jpg'); original_image2=imread ('input2.jpg'); figure() subplot(3,3,1),imshow(original_image1),title('Original Source...
Principal Component Analysis using Matlab
PCA is a way of identifying patterns in data, and expressing the data in such a way as to highlight their similarities and differences. Below are the steps of the algorithm: close all; % clear all; clc; % data = load('Data/eeg.mat'); % data = data.data{1,2}; Step 1 – Initialize the dataset, 6 vectors of 32 sample data % % Step 1 - Initialize the dataset, 6 vectors of 32 sample data % X =...
Literature Review in Speech Emotion Recognition
Introduction Speech is one of the fastest and most natural ways of communication between humans. The speech signal contains not only the message but also necessary information like the emotions of the speaker [1]. Therefore, Speech emotion recognition (SER) is a research field that based on speech recognition but deals with the recognizing the emotional state of the speaker. Speech emotion...
Literature Review of Deep Machine Learning for feature extraction
Abstract Feature extraction is a crucial part of many tasks. In recent years, deep learning approaches have achieved significant importance as a way of constructing hierarchical representations from unlabeled data. Understanding how to recognize complex, high-dimensional data is one of the greatest requests of our time. Deep Machine Learning have showed us that there is an efficient and accurate...
What is Kalman Filter
Kalman filtering, also known as linear quadratic estimation (LQE), is an algorithm that uses a series of measurements observed over time, containing statistical noise and other inaccuracies, and produces estimates of unknown variables that tend to be more precise than those based on a single measurement alone. The filter is named after Rudolf E. Kálmán, one of the primary developers of its theory...
Inverse Kinematics using Fuzzy Logic
What Is Inverse Kinematics? Kinematics is the science of motion. In a two-joint robotic arm, given the angles of the joints, the kinematics equations give the location of the tip of the arm. Inverse kinematics refers to the reverse process. Given a desired location for the tip of the robotic arm, what should the angles of the joints be so as to locate the tip of the arm at the desired location...
What is Particle Swarm Optimization?
Particle swarm optimization (PSO) is a population based stochastic optimization technique developed by Dr. Eberhart and Dr. Kennedy in 1995, inspired by social behavior of bird flocking or fish schooling. PSO shares many similarities with evolutionary computation techniques such as Genetic Algorithms (GA). The system is initialized with a population of random solutions and searches for optima by...
Fuzzy Logic? Why? Where?
Today many household appliances have fuzzy logic built into them to make their use easier. You can find fuzzy logic in shower heads, rice cookers, vacuum cleaners, and just about everywhere. Here is a list of general observations about fuzzy logic: Fuzzy logic is conceptually easy to understand. The mathematical concepts behind fuzzy reasoning are very simple. What makes fuzzy nice is the...
