Cognitive decisions that do not match the expected output value are weakened, reducing the possibility of readopting these solutions under the same conditions [4]. View chapter Book 2023, Spatial Cognitive Engin
We show how the attention mechanisms can help deep learning better understand the correlations between NILM features and how generative pattern recognition can help capture the underlying probability densities of the features thereby improving the NILM accuracy for cutting-edge deep learning solutions. ...
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Tap the power of neural network and genetic algorithm artificial intelligence software techniques to transform your problems into solutions. Easily apply artificial intelligence, neural networks and genetic algorithms yourself with low cost software, free assistance and advice from a company that has been...
The deep predictive coding network proposed in ref.8(PredNet) consists of repeated, stacked modules, where each module generates a prediction of its own feedforward inputs, computes errors between these predictions and the observed inputs, and then forwards these error signals to subsequent layers ...
The Fraunhofer Neural Network Encoder/Decoder Software (NNCodec) is an efficient implementation of NNC (Neural Network Coding / ISO/IEC 15938-17 or MPEG-7 part 17), which is the first international standard on compression of neural networks. NNCodec provides an encoder and decoder with the foll...
In this chapter, we will look at the fundamental concepts underlying RNNs, the main problem they face (namely, vanishing/exploding gradients, discussed in Chapter 2), and the solutions widely used to fight it: LSTM and GRU cells. Along the way, as always, we will show how to implement ...
ESN is a new type of neural network proposed by Jaeger [1] in 2001. It not only overcomes the computational complexity, training inefficiency, and difficulty of the practical application of RNN but also avoids the problem of locally optimal solutions. ESN mimics the structure of recursively ...
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Fig. 6. The impact of the neuron numbers in the hidden layer on the performance of the neural network [39]. Yang et al. [40] in 2013 have studied the removal of color from solutions containing metal-complex dye acid black 172 using the adsorption using bamboo biochar. They have also co...