A Theoretical Study of Linear and Nonlinear Equalization in Nonlinear Magnetic Stirage Channels  

Oleh:

Moon, J. ; Nair, S. K.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 8 no. 5 (1997), page 1106-1118.
Topik: magnetic; linear; equalization; magnetic stirage

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36.2 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

We present methods to systematically design a feedforward neural - network detector from the knowledge of the channel characteristics. Its performance is compared with the conventional linear equalizer in a magnetic recording channel suffering from signal - dependent noise and nonlinear intersymbol interference. The superiority of the non linear schemes are clearly observed in all cases studied, especially in the presence of severe nonlinearity and noise. We also show that the decision boundaries formed by a theoretically derived neural - network classifier are geometrically close to those of a neural network trained by the backpropagation algorithm. The approach in this work is suitable for quantifying the gain in using a neural - network method as opposed to linear methods in the classification of noisy patterns.

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