Back Propagation Neural Network(BPNN) and Sigmoid Activation Function in Multi-Layer Networks

Abstract

Back propagation neural network are known for computing the problems that cannot easily be computed (huge datasets analysis or training) in artificial neural networks. The main idea of this paper is to implement XOR logic gate by ANNs using back propagation neural network for back propagation of errors, and sigmoid activation function. This neural network to map non-linear threshold gate. The non-linear used to classify binary inputs (x1, x2) and passing it through hidden layer for computing coefficient_errors and gradient_errors (Cerrors, Gerrors), after computing errors by (ei = Output_desired- Output_actual) the weights and thetas (ΔWji = (α)(Xj)(gi), Δϴj = (α)(-1)(gi)) are changing according to errors. Sigmoid activation function is = sig(x)=1/(1+e-x) and Derivation of sigmoid is = dsig(x) = sig(x)(1-sig(x)). The sig(x) and Dsig(x) is between 1 to 0.

Review on Deep Learning and Neural Network Implementation for Emotions Recognition

“…• This implementation by default detects emotions on all faces in the webcam feed. With a simple 4layer CNN, the test accuracy reached 63.2% in 50 epochs [1]. preprocessing in the dataset_prepare.py file which can be used for reference [10].…”

“…You may now wear one of them around your wrist that senses the pulse, temperature, level of sweating and the number of steps that you walked today, but what if we used these sensors to sense our emotions and help us to have Be able to express and recognize our emotions in a way that facilitates dealing with others, for example, why don't we use technology to read our mood for example? When we are exhausted and tired, there is a device that reads this and others know about it without the person having to speak [1]. Emotions are very important in our lives, they are the most influencing things on our memories, and on our decisions that we make on a daily basis, and since we now have devices that help us know the way in a strange country, or to translate languages instantly, and devices that predict when we arrive at home in order to save us energy consumption From heat and electricity, we will also have devices that help us better sense our emotions than we are now.…”

“…Hence, building a system that is capable of both face detection and emotion recognition has been a crucial area of research [3]. It is a well-established fact that human beings are responsible for the depiction of six basic emotions, namely happiness, anger, surprise, sadness, fear, and disgust [1]. These primary emotions form the primary classification of the study of human emotional responses.…”

“…Other factors also contribute to the recognition of a person's emotional state such as voice, body language, gestures or even the direction of the gaze. Emotion recognition, therefore, demands a more precise knowledge of all these factors together with contextual information to convey more accurate results [1]. Facial emotional recognition is essentially pattern recognition and involves finding regularities in the set of data being analyzed.…”

“…he other method is appearance-based where attributes such as intensities, pixel values, and histograms are considered. After exhaustive training is done with the help of prelabeled datasets, machine learning techniques are applied to detect emotions [1].…”