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Convolutional neural network (CNN) has been successfully used in many fields including image recognition. CNN is composed of input, convolution, pooling, hidden and output layers, and the weights and biases between layers except the ones between convolution and pooling layers are acquired by learning. In comparison to the conventional neural networks, the learning cost of CNN is higher, and the learning...
A neural representation of combinational logic circuit is proposed, called `Logical Neural Network' (LNN). LNN is a feed-forward neural network (NN) where the weights of the network indicate the connections of digital circuit. The logic operations of the circuit such as AND, OR, NOR etc are performed with the neurons of LNN. A modification of Simple Genetic Algorithm (mSGA) is applied to design and...
Multilayer feed-forward neural network is widely used based on minimization of an error function. Back propagation is a famous training method used in the multilayer networks but it often suffers from the problems of local minima and slow convergence. These problems take place due to the gradient behavior of mostly used sigmoid activation function (SAF). Weight update becomes zero when activation...
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