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In order to reduce the complexity and enhance the performance of the Bayesian equalizer using the radial basis function (RBF) network, a new equalizer using the RBF network with a nonlinear multilayer combiner (RNEQ) is proposed. The RNEQ is applied to a digital storage system in which the primary element of impairment is nonlinear distortion due to partial erasure. From computer simulation results, the RNEQ with almost 70% reduced structural complexity over the conventional equalizer using RBF

This paper presents nonlinear blind equalization techniques using an adaptive bilinear polynomial filter. Two types of blind adaptive bilinear polynomial equalizers with reduced bilinear terms are proposed. One is a blind bilinear polynomial decision feedback equalizer using conventional constant modulus algorithm, which uses previous detected symbols. The other is a blind predictive constant modulus bilinear decision feedback equalizer, which uses error signals. In proposed equalizers, the inpu

In order to reduce the complexity of a radial basis function (RBF) network as a multiuser demodulator and an equalizer, we propose a simplified hybrid neural network architecture. The proposed neural network, which is called RN, has the structure of combining a radial basis function network with multilayer perceptrons (MLPs). The RBF network yields the linear combining output of the hidden layer while the proposed hybrid neural network produces the output using nonlinear combining techniques. Fr

A new neural equalizer is proposed in order to compensate for intersymbol interference and to mitigate nonlinear distortions in digital magnetic recording systems. The proposed equalizer uses the quadratic sigmoid function as the activation function. The performance of the proposed equalizer is compared to those of a decision-feedback equalizer (DFE) and a neural decision feedback equalizer (NDFE) in terms of bit-error rate in nonlinear digital magnetic recording channels. Simulation results dem

As semiconductor packaging technologies face limitations, through-silicon via (TSV) technology has emerged as a key solution to extending Moore’s law by achieving high-density, high-performance microelectronics. TSV technology enables enhanced wiring density, signal speed, and power efficiency, and offers significant advantages over traditional wire-bonding techniques. However, achieving fine-pitch and high-density interconnects remains a challenge. Solder flip-chip microbumps have demonstrated

In this letter, a new adaptive beamforming assisted receiver based on sparse Bayesian learning is proposed. We consider a general probabilistic Bayesian learning framework for obtaining sparse solutions to adaptive beamforming assisted receivers to improve the performance of an adaptive beamforming assisted receiver based on the minimum mean squared error (MMSE) scheme. Simulation experiments show that the bit error rate (BER) performance of the sparse Bayesian beamforming receiver shows an outs

In order to reduce the complexity and enhance the performance of the Bayesian equalizer (REQ) using the radial basis function (RBF) network, a new equalizer (RNEQ) using the RBF network with a nonlinear multilayer combiner is proposed. The proposed RNEQ produces the output using nonlinear multilayer combiner. The RNEQ is applied to a digital communication system and a nonlinear magnetic storage system. From computer simulation results, the RNEQ with almost 70% reduced structure over the REQ show

In order to compensate for severe intersymbol interference (ISI) and combat nonlinear distortions in digital magnetic recording systems, Bayesian equalizer using the radial basis function (RBF) network, REQ, is applied as a channel equalizer to a data storage system using partial erasure (PE) model. It can be seen from various computer simulation results that the REQ has a more complex structure than a conventional linear equalizer (LE) while the bit-error-ratio (BER) of the REQ is lower than th

This study was effect of self - esteem of hotel employees affects service orientation and customer orientation, In order to examine the effect of service orientation on customer orientation, we conducted research based on the results of previous studies.BR The survey was conducted from August 01, 2018 to August 30, 2018 for 30 days. A total of 250 questionnaires were distributed, 50 of which were selected from 5 luxury hotels in Seoul, and 238 questionnaires were collected. A total of 221 valid

The multivariate polynomial model provides an effective way to describe complex nonlinear input-output relationships since it is tractable for optimization, sensitivity analysis, and prediction of confidence intervals. However, for high-dimensional and high-order problems, multivariate polynomial model becomes impractical due to its huge number of product terms. Therefore, multivariate polynomial model cannot be applied for nonlinear channel equalization problems. This is especially true for the

본 연구는 외식 종사원의 고용환경변화가 직무불안정성 및 직무스트레스에 대해 어떠한 영향관계에 있는지 알아보고, 또한 자아탄력성이 어떠한 조절효과를 나타내는지 알아보기 위하여 선행연구들을 중심으로 연구를 진행했다. 설문 조사는 2019년 08월 26일부터 09월 09일까지 2주간 시행하였으며 설문 대상은 서울·수도권 외식 프랜차이즈 종사원을 대상으로 총 242부의 유효한 설문지를 최종적인 분석 자료로 이용하였다. 본 연구의 결과를 요약하면 다음과 같다. 첫째, 외식 종사원의 고용환경변화와 직무상실 가능성의 다중회귀분석의 결과는 정리해고보편화(β= .352, P<001), 조직구조의 변화(β=.523, P<.001)로 종속변수인 직무불안정성에 대하여 유의한 정(+)의 영향 관계임을 알 수 있었으며. 둘째, 외식 종사원의 고용환경변화와 무력감의 다중회귀분석의 결과는 정리해고보편화 (β= .650, P<001), 조직구조의 변화(β=.099, P<.05)로 종속변수인 직무불안정성에 대해 유