Object recognition and classification is a common problem facing computers. There are many shortcomings in proper identification of an object when it comes to computer algorithms. A very common process used to deal with classification problems is neural networks. Neural networks are modelled after the human brain and the neuron firings that occur when an individual looks at an image and identif...

We present probabilistic neural programs, a framework for program induction that permits flexible specification of both a computational model and inference algorithm while simultaneously enabling the use of deep neural networks. Probabilistic neural programs combine a computation graph for specifying a neural network with an operator for weighted nondeterministic choice. Thus, a program describ...

In this paper a Neural Networks (NN) is proposed for transient stability prediction. Transient stability of a power system is first determined based on the generator relative rotor angles procured from time domain simulation outputs. Simulations were carried out on a single machine infinite bus system by considering three phase short circuit fault on the system. The data collected from the time...

We present probabilistic neural programs, a framework for program induction that 1 permits flexible specification of both a computational model and inference algo2 rithm while simultaneously enabling the use of deep neural networks. Probabilistic 3 neural programs combine a computation graph for specifying a neural network with 4 an operator for weighted nondeterministic choice. Thus, a program...

In power system, operation and fortification detection and classification of current and voltage conflict is a significant assignment. In this paper, a measurement system of some transient disturbances based on Artificial Neural Networks will be presented.This paper presents a new advance for classifying the proceedings that stand for or direct to the dreadful conditions of power quality. A pro...

One of the most important topics in the sonar sound data processing is proposing a powerful classifier to detect the sound source. In this paper we propose a classifier with proper accuracy. First, proper features should be extracted from sound data; Features could extract from time or frequency domains. Whenever fastness is important, time features are most effective. Otherwise, frequency doma...

We propose a method for discrimination and classification of ovarian with benign, malignant and normal tissue using independent component analysis and neural networks. The method was tested for a proteomic patters set from A database, and radial basis functions neural networks. The best performance was obtained with probabilistic neural networks, resulting I 99% success rate, with 98% of specif...

We propose a method for discrimination and classification of ovarian with benign, malignant and normal tissue using independent component analysis and neural networks. The method was tested for a proteomic patters set from A database, and radial basis functions neural networks. The best performance was obtained with probabilistic neural networks, resulting I 99% success rate, with 98% of specif...

Perineuronal nets (PNNs) are specialized extracellular matrix molecules that are associated with the closing of the critical period, among other functions. In the adult brain, PNNs surround specific types of neurons, however the expression of PNNs in the auditory system of the mouse, particularly at the level of the midbrain and forebrain, has not been fully described. In addition, the associat...