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The difference is that our state vector has the memory of input stimulus, in contrast, the state vector given in Ref. [18] was internally generated in a memory task.
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From the perspective of dynamic system theory, these states of hidden neuron nodes serve as a memory of the input audio feature and are termed as echoes of the input history.
Extending the filter to two frequencies requires more data in the form of memory of the input waveform.
The structure of the decoder is modified to reduce the amount of memory of the input buffer, the metric memory, the interleaver and the deinterleaver though it is based on the SW-MAP scheme.
Thus, the device is considered to be having an internal memory of the input voltage.
The memory of the input matrix can be re-used in inverse matrix calculation and the output matrices re-use the memory that was allocated to calculating the inverse matrix.
The input layer is constituted by a set of cue selective neurons that compute short term memories (STM) of input stimuli.
LSTM models incorporate a hidden state that acts as a memory of previous inputs, providing an advantage when interpreting time series data such as machine health.
Rather, recurrent networks process a time-dependent signal one frame at a time, using feedback connections that create a memory of previous inputs.
In order to improve the performance of the conventional associative memory network, a novel associative memory network composed of input layer, computing layer, associative layer and output layer is proposed.
Using infinitesimal perturbations suppresses the residual error, but such perturbations are less robust against uncertainty and noise in an eligibility trace, which is a memory of perturbation and input.
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CEO of Professional Science Editing for Scientists @ prosciediting.com