In this paper, we investigate the relation between Artificial Neural Networks (ANNs) and networks of populations of spiking neurons. The activity of an artificial neuron is usually interpreted as the firing rate of a neuron or neuron population. Using a model of the visual cortex, we will show that this interpretation runs into serious difficulties. We propose to interpret the activity of an ar...

The paper presents an agent based model of the Aedes aegypti mosquito, which considers mosquito population dynamics and a speci c population control strategy, as well the dengue propagation in mosquito (vector) and human (host) populations. More speci cally, this study concerns the impact that the RIDL strategy (Release of Insects carrying a Dominant Lethal gene) has on the infection period amo...

The problem in face recognition is to find the best match of an unknown image against a database of face models or to determine whether it does not match any of them well. In this method, we use back propagation neural network for implementation. It is an information processing system that has been developed as a generalization of the mathematical model of human recognition. The function of a n...

This paper presents one of the soft computing methods, specifically the artificial neural network technique, that has been used to model the temperature dependence of dynamic mechanical properties and visco-elastic behavior of widely exploited thermoplastic polyurethane over the wide range of temperatures. It is very complex and commonly a highly non-linear problem with no easy analytical metho...

In this paper, Multilayer Feed Forward Artificial Neural Network with weight initialization method is Proposed for Image Compression. Image compression helps to reduce the storage space and transmission cost. Artificial Neural network (ANNs) is a training algorithm has used to compress the image. Artificial neural network is exceptionally Feed Forward Back propagation neural network (FFBPNN) in...

The problem in face recognition is to find the best match of an unknown image against a database of face models or to determine whether it does not match any of them well. In this method, we use back propagation neural network for implementation. It is an information processing system that has been developed as a generalization of the mathematical model of human recognition. The function of a n...

Recent developments show that Multiply Sectioned Bayesian Networks (MSBNs) can be used for diagnosis of natural systems as well as for model-based diagnosis of artificial systems. They can be applied to single-agent oriented reasoning systems as well as multiagent distributed reasoning systems. Belief propagation between a pair of subnets plays a central role in maintenance of global consistenc...

drying characteristics of green pea (pisum satium) with an initial moisture content of 76% (db) was studied in a fluidized bed dryer assisted by microwave heating. four drying air temperatures (30, 40, 50 and 60ºc) and five microwave powers (180, 360, 540, 720 and 900w) were adopted. several experiments were conducted to obtain data for sample moisture content versus drying time. the results sh...

Card games are interesting for many reasons besides their connection with gambling. Bridge is being a game of imperfect information, it is a well defined, decision making game. The estimation of the number of tricks to be taken by one pair of bridge players is called Double Dummy Bridge Problem (DDBP). Artificial Neural Networks are Non – Linear mapping structures based on the function of the h...

This paper investigates the ability of several alternate models of Artificial Neural Network (ANN) to predict the probability of occurrence of Hypertension (HT) in a mixed patient population. To do this a two-layer feed-forward neural network with 13 inputs and 1 output was created with a single hidden layer . Different types of networks structures, such as NEWFF (feed-forward back propagation ...