An optimum multilayer perceptron neural receiver for signal detection
| Autor: | J.W. Watterson |
|---|---|
| Rok vydání: | 1990 |
| Předmět: |
Bandlimiting
Computer Networks and Communications Computer science Computer Science::Neural and Evolutionary Computation Monte Carlo method Machine learning computer.software_genre Signal symbols.namesake Artificial Intelligence Detection theory Computer Science::Information Theory Artificial neural network business.industry General Medicine Backpropagation Computer Science Applications Amplitude Additive white Gaussian noise Multilayer perceptron symbols Artificial intelligence business computer Algorithm Software |
| Zdroj: | IEEE transactions on neural networks. 1(4) |
| ISSN: | 1045-9227 |
| Popis: | The M-input optimum likelihood-ratio receiver is generalized by considering the case of different signal amplitudes on the receiver primary input lines. Using the more general likelihood-ratio receiver as a reference, an equivalent optimum multilayer perceptron neural network (or neural receiver) is identified for detecting the presence of an M-dimensional target signal corrupted by bandlimited white Gaussian noise. Analytical results are supported by Monte Carlo simulation runs which indicate that the detection capability of the proposed neural receiver is not sensitive to the level of training or number of patterns in the training set. > |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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