Search Results

Now showing 1 - 6 of 6

Some of the metrics are blocked by your
consent settings
Optimal neuro-fuzzy equalizers for nonlinear channels of the perpendicular magnetic recording system
(2021-01-01)
Wongsathan, Rati
;
Supnithi, Pornchai
Nonlinear distortions caused by partial erasure and nonlinear transition shifts interacting with inter-symbol interference, are a major hindrance to data storage systems, since they degrade detector performance. This work aims to design and optimize the neuro-fuzzy equalizer (NFE) using the multi-objective genetic algorithm (MOGA) to detect nonlinear high-density magnetic recording (MR) channels. Through the GA-assisted back-propagation algorithm and least mean square optimization, the complexity in terms of decision rules is reduced by 25% and significantly provides 65% lower signal processing computation. When applied to the perpendicular (MR) system, the proposed NFE outperforms existing equalizers such as the neural network-based equalizer, fuzzy logic equalizer, and conventional NFE for the Volterra and jitter media noise channels using 1-3 dB and 1.5-3.5 dB signalto-noise ratio gains at the bit-error-rate of 10−4, respectively. Furthermore, compared to the other models, the NFE provides a more effective output mean square error performance for retrieving the original bit data.
Some of the metrics are blocked by your
consent settings
Fuzzy logic-based adaptive equaliser for nonlinear perpendicular magnetic recording channels
(2019-06-04)
Wongsathan, Rati
;
Supnithi, Pornchai
This paper proposes the fuzzy logic equaliser (FLE) for the detection of non-linear perpendicular magnetic recording (PMR) channels. The multi-objective genetic algorithm (MOGA) is utilised to optimise all of the fuzzy parameters and reduce the complexity while maintaining the accuracy. By means of this optimisation, the total number of fuzzy rules is significantly reduced about 44%. The bit error rate (BER) performance of the proposed FLEs are compared with those of the conventional detector and traditional non-linear equalisers for Volterra channel, in presence of non-linear amplitude distortions in high-density PMR channels. The proposed FLE outperforms existing detectors by 1 to 12 dB SNR gains. Furthermore, the complexity in terms of multiplication counts per execution and reliability of detectors with regard to the number of system parameters through the Akaike's information criterion (AIC) are assessed to verify the effectiveness of the proposed FLEs. An extension to PMR channel with jitter noise proves the robustness of the proposed FLEs.
Some of the metrics are blocked by your
consent settings
The Performance of Neuro-Fuzzy Detection on Nonlinear Magnetic Recording Channels
(2019-06-01)
Wongsathan, Rati
;
Supnithi, Pornchai
This work proposes the nonlinear detection scheme using an adaptive neuro-fuzzy equalizer (NFE) for the nonlinear perpendicular magnetic recording (PMR) channels. Based on a Volterra model of PMR channels at high normalized recording density, the proposed NFE is derived in order to improve the system performance. The bit error rate (BER) performance of the proposed NFE is compared with that of the existing equalizer, i.e., multilayered perceptron neural network equalizer (MLPNNE) and fuzzy logic equalizer (FLE). At the normalized recording density of 3, the proposed NFE outperforms the others by 1 to 4 dB SNR gains.
Some of the metrics are blocked by your
consent settings
Performance of the hybrid MLPNN based VE (h MLPNN-VE) for the nonlinear PMR channels
(2018-05-01)
Wongsathan, Rati
;
Phakphisut, Watid
;
Supnithi, Pornchai
This paper proposes a hybrid of multilayer perceptron neural network (MLPNN) and Volterra equalizer (VE) denoted hMLPNN-VE in nonlinear perpendicular magnetic recording (PMR) channels. The proposed detector integrates the nonlinear product terms of the delayed readback signals generated from the VE into the nonlinear processing of the MLPNN. The detection performance comparison is evaluated in terms of the tradeoff between the bit error rate (BER), complexity and reliability for a nonlinear Volterra channel at high normalized recording density. The proposed hMLPNN-VE outperforms MLPNN based equalizer (MLPNNE), VE and the conventional partial response maximum likelihood (PRML) detector.
Some of the metrics are blocked by your
consent settings
Neural networks equalizers for nonlinear magnetic recording channels
(2017-11-03)
Wongsathan, Rati
;
Phakphisut, Watid
;
Supnithi, Pomchai
Nonlinear distortion in perpendicular magnetic recording channels is known to degrade the overall system performance. In this work, we propose two nonlinear equalizers based on neural network (NN). One involves symbol decision of received signals using a multilayer perceptronNN equalizer (MLPNNE) only, and the other includes the NN equalizer to shape received signal to a partial-response target followed by a maximum likelihood (ML) sequence detection scheme using Viterbi algorithm (ML-MLPNNE). When applied to nonlinear channels generated by Volterra model (VM), it is shown that these two proposed equalizers give similar BER performances. At the BER of 10<sup>-4</sup>, they provide about 10-dB SNR gains over the conventional partial-response maximum likelihood (PRML) technique. The MLPNNE with the simple threshold needs simpler implementation than the ML-MLPNNE although noise correlation is a disadvantage.
Some of the metrics are blocked by your
consent settings
Channel response of HAMR with linear temperature-dependent coercivity and remanent magnetization
(2012-10-02)
Wongsathan, Rati
;
Supnithi, Pornchai
In this work, we derive the Thermal-WilliamsComstock model for the heat-assisted magnetic recording channels. The coercivity and remanent magnetization have linear relationship with the temperature. The transition width and transition centres can be obtained for various cases. Together with the microtrack model, the generation of transition response, dibit response as well as the readback of pseudorandom sequence with and without jitter noise can be achieved. © 2012 IEEE.

KMITL

Browse

Filters

Settings

Sort By

Results per page

Search Results