NOISE-ENHANCED CONVOLUTIONAL NEURAL NETWORKS

摘要

A learning computer system may include a data processing system and a hardware processor and may estimate parameters and states of a stochastic or uncertain system. The system may receive data from a user or other source; process the received data through layers of processing units, thereby generating processed data; apply masks or filters to the processed data using convolutional processing; process the masked or filtered data to produce one or more intermediate and output signals; compare the output signals with reference signals to generate error signals; send and process the error signals back through the layers of processing units; generate random, chaotic, fuzzy, or other numerical perturbations of the received data, the processed data, or the output signals; estimate the parameters and states of the stochastic or uncertain system using the received data, the numerical perturbations, and previous parameters and states of the stochastic or uncertain system; determine whether the generated numerical perturbations satisfy a condition; and, if the numerical perturbations satisfy the condition, inject the numerical perturbations into the estimated parameters or states, the received data, the processed data, the masked or filtered data, or the processing units.

主权项

1. A learning computer system that estimates parameters and states of a stochastic or uncertain system comprising a data processing system that includes a hardware processor that has a configuration that:
receives data from a user or other source; processes the received data through layers of processing units, thereby generating processed data; applies masks or filters to the processed data using convolutional processing; processes the masked or filtered data to produce one or more intermediate and output signals; compares the output signals with reference signals to generate error signals; sends and processes the error signals back through the layers of processing units; generates random, chaotic, fuzzy, or other numerical perturbations of the received data, the processed data, or the output signals; estimates the parameters and states of the stochastic or uncertain system using the received data, the numerical perturbations, and previous parameters and states of the stochastic or uncertain system; determines whether the generated numerical perturbations satisfy a condition; and if the numerical perturbations satisfy the condition, injects the numerical perturbations into the estimated parameters or states, the received data, the processed data, the masked or filtered data, or the processing units.