Sentence examples for between the input layers from inspiring English sources
The connections between the input layers and the entorhinal cortex serve the integration of object and spatial-configural information.
The two connectivity levels contribute differently to the evaluated dysfunctions: a lack of contextual constraints, both in lexical disambiguation and in the list learning task, is largely due to the reduced connectivity between the input layers and the entorhinal cortex.
The difference in the latency of activation (defined as the time of the peak of the PSTH, compare also Sakata and Harris 2009) between the input layers and the output layers in our network is with around 2 3 ms below the experimentally observed latencies (5 10 ms according to Schroeder et al. (1998); Sakata and Harris (2009)).
The layers between the input layer and the output layer are called hidden layers and usually contain nonlinear elements.
The weight matrixes between the input layer, the hidden layer, and the output layer are adjusted using back propagation algorithm.
Each BP neural network has three layers, and the weight matrixes between the input layer, the hidden layer, and the output layer are adjusted using back propagation algorithm.
LIN is implemented by inserting an additional hidden layer with linear activation between the input layer and the first hidden layer.
The connections between the input layer and the middle or hidden layer contain weights [Eq. (2)], which are usually determined through training the system.
The architecture reduces the number of weights by a great number as there are no formal connections between the input layer and the principal component layer.
Each individual consists of connection weights between the input layer and hidden layer, thresholds in the hidden layer, connection weights between the hidden layer and output layer, and the threshold in the output layer.
Finally, the unknown nonlinearities including the input saturation dynamics are estimated by using an echo state network, which is easily trained without adjusting the weights between the input layer and the hidden layer.
