Simplified multi-track detection schemes using a priori information for bit patterned media recording

2012 ◽  
Vol 111 (7) ◽  
pp. 07B920
Author(s):  
Gyuyeol Kong ◽  
Sooyong Choi
Keyword(s):  
A Priori ◽  
A Priori Information ◽  
Bit Patterned Media ◽  
Patterned Media ◽  
Priori Information ◽  
Detection Schemes

scholarly journals Iterative Signal Detection Scheme Using Multilayer Perceptron for a Bit-Patterned Media Recording System

2020 ◽  
Vol 10 (24) ◽  
pp. 8819
Author(s):  
Seongkwon Jeong ◽  
Jaejin Lee
Keyword(s):  
Signal Detection ◽  
Data Storage ◽  
Multilayer Perceptron ◽  
A Priori ◽  
Magnetic Data ◽  
Bit Patterned Media ◽  
Detection Scheme ◽  
Patterned Media ◽  
Storage Density ◽  
Priori Information

Because of the physical and engineering problems of conventional magnetic data storage systems, bit-patterned media recording (BPMR) is expected to be a promising technology for extending the storage density to beyond 1 Tb /in2. To increase the storage density in BPMR systems, the separation between islands in both down- and cross-track directions must be reduced; this reduction results in two-dimensional interference from neighboring symbols in those directions, which is a major performance degradation factor in BPMR. Herein, we propose an iterative signal detection scheme between a Viterbi detector and a multilayer perceptron to improve the performance of a BPMR system. In the proposed signal detection scheme, we use the modified output of a multilayer perceptron as a priori information to improve equalization and extrinsic information to decrease the effect of intertrack interference.

Resolution Enhancement of Composite Spectra with Fractal Noise in Derivative Spectrometry

2000 ◽  
Vol 54 (5) ◽  
pp. 721-730 ◽  
Author(s):  
S. S. Kharintsev ◽  
D. I. Kamalova ◽  
M. Kh. Salakhov
Keyword(s):  
A Priori ◽  
Resolution Enhancement ◽  
Numerical Differentiation ◽  
A Priori Information ◽  
Experimental Ir ◽  
Composite Spectra ◽  
Self Similar ◽  
Priori Information ◽  
Fractal Noise ◽  
Derivative Spectrometry

The problem of improving the resolution of composite spectra with statistically self-similar (fractal) noise is considered within the framework of derivative spectrometry. An algorithm of the numerical differentiation of an arbitrary (including fractional) order of spectra is produced by the statistical regularization method taking into account a priori information on statistical properties of the fractal noise. Fractal noise is analyzed in terms of the statistical Hurst method. The efficiency and expedience of this algorithm are exemplified by treating simulated and experimental IR spectra.

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