Neural network error correcting decoders for block and convolutional codes

The use of neural networks as error correcting decoders is described. It is shown that the neural networks may offer advantages in electronic countermeasure (ECM) environments in which the convolutional design assumptions of additive white Gaussian noise (AWGN) and a binary symmetric channel (BSC) a...

Ausführliche Beschreibung

Bibliographische Detailangaben

Hauptverfasser:	Caid, W.R., Means, R.W.
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Additive white noise AWGN Character generation Computational modeling Convolutional codes Decoding Electrochemical machining Error correction codes Jamming Neural networks
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