• Journal of information and communication convergence engineering
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• v.9 no.2
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• pp.183-186
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• 2011

In this work, we consider imperfectness of feedback channels in the adaptive transmission scheme which was previously studied with an assumption of error-free feedback channels. New method of mapping the modulation index into the feedback channel symbols and quantifying feedback error over fading channels are proposed. The presented method and results are expected to offer valuable tools for the system designer to efficiently implement adaptive diversity schemes to compensate for the performance degradation due to feedback error.

• Journal of International Academy of Physical Therapy Research
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• v.9 no.4
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• pp.1602-1607
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• 2018

This study examined the correlation between power error (PE) and velocity error (VE) according to the condition and frequency of self-controlled feedback (SCF) during knee extension. One hundred participants were randomly assigned to 30% SCF, 70% SCF, 30% yoked feedback (YF), 70% YF and control group, respectively. The SCF group was provided with feedback when they requested it, whereas the YF group did not influence the feedback schedule. Participants in the control group were not given any visual feedback during the experiment. The isotonic, isometric, and isokinetic dynamometer (PRIMUS RS, BTE, USA) was used to measure the power and velocity error during knee extension. The collected data was analyzed using a Pearson test and SPSS 21.0. The correlation between PE and VE according to the condition and frequency of feedback on each phase during knee extension was significant. Both PE and VE were significantly higher when the feedback was provided with high frequency, passive, and no feedback. Our study suggests that application of SCF can help to improve the proprioception of the healthy person while reducing errors through low frequency and active feedback.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.12C
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• pp.753-758
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• 2011

The constant modulus algorithm (CMA) widely used in blind equalization applications minimizes the averaged power of constant modulus error (CME) defined as the difference between an instant output power and a constant modulus. In this paper, a decision feedback version of the linear blind algorithm based on maximization of the zero-error probability for CME is proposed. The Gaussian kernel of the maximum zero-error criterion is analyzed to have the property to cut out excessive CMEs that may be induced from severely distorted channel characteristics. Decision feedback approach to the maximum zero-error criterion for CME is developed based on the characteristic that the Gaussian kernel suppresses the outliers and this prevents error propagation to some extent. Compared to the linear algorithm based on maximum zero-error probability for CME in the simulation of blind equalization environments, the proposed decision feedback version has superior performance enhancement particularly in cases of severe channel distortions.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.8 s.338
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• pp.17-24
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• 2005

This paper proposes a Decision Feedback Equalizer (DFT) with an error feedback filter for blind channel equalization. The proposed equalizer uses Least Mean Square(LMS) Algorithm and Multi-Modulus Algorithm (MMA), and has been designed for 64/256 QAM constellations. The existing MMA equalizer uses either two transversal filters or feedforward and feedback filers, while the proposed equalizer uses feedforward, feedback and error feedback filters to improve the channel adaptive performance and to reduce the number of taps. The proposed equalizer has been simulated using the $SPW^{TM}$ tool and it shows performance improvement. It has been modeled by VHDL and logic synthesis has been performed using the $0.25\;\mu m$ Faraday CMOS standard cell library. The total number of gates is about 190,000 gates. The proposed equalizer operates at 15 MHz. In addition, FPGA vertification has been performed using FPGA emulation board.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.219-222
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• 2017

This study aimed to demonstrate the effect of feedback type on users' subjective responses in a voice user interface. Feedback type is classified depend on information characteristic it involves; verification feedback and elaboration feedback. Error type is categorized as recognition error and performance error. Users' subjective assessment about system, feedback acceptance, and intention to use were measured as dependent variables. The results of experiment showed that feedback type has impacts on the subjective assessment(likeability, habitability, system response accuracy) of VUI, feedback acceptance, and intention to use. the results also demonstrated an interaction effect of feedback type and error type on the feedback acceptance. It leads to the conclusion that VUI should be designed with the elaboration feedback about error situation.

• International Journal of Contents
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• v.5 no.3
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• pp.65-70
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• 2009

This paper describes ongoing work on the correction of adverb errors committed by Korean learners studying English as a foreign language (EFL), using an automated English writing assessment system. Adverb errors are commonly found in learners 'writings, but handling those errors rarely draws an attention in natural language processing due to complicated characteristics of adverb. To correctly detect the errors, adverbs are classified according to their grammatical functions, meanings and positions within a sentence. Adverb errors are collected from learners' sentences, and classified into five categories adopting a traditional error analysis. The error classification in conjunction with the adverb categorization is implemented into a set of mal-rules which automatically identifies the errors. When an error is detected, the system corrects the error and suggests error specific feedback. The feedback includes the types of errors, a corrected string of the error and a brief description of the error. This attempt suggests how to improve adverb error correction method as well as to provide richer diagnostic feedback to the learners.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.197-200
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• 1996

This paper considers feedback error learning neural networks for robot manipulator control. Feedback error learning proposed by Kawato [2,3,5] is a useful learning control scheme, if nonlinear subsystems (or basis functions) consisting of the robot dynamic equation are known exactly. However, in practice, unmodeled uncertainties and disturbances deteriorate the control performance. Hence, we presents a robust feedback error learning scheme which add robustifying control signal to overcome such effects. After the learning rule is derived, the stability is analyzed using Lyapunov method.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1981-1986
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• 2004

In this study, the basic motor control system had been investigated. The controller for this study consists of two main parts, a feedforward controller part and a feedback controller part. Each part will deals with different control problems. The feedback controller deals with robustness and stability, while the feedforward controller deals with response speed. The feedforward controller, used to solve the tracking control problem, is adaptable. To make such a tracking perfect, an adaptive law based on Feedback Error Learning (FEL) is designed so that the feedforward controller becomes an inverse system of the controlled plant. The novelty of FEL method lies in its use of feedback error as a teaching signal for learning the inverse model. The theory in $H^{\infty}$-Control is selected to be applied in the feedback part to guarantee the stability and solve the robust stabilization problems. The simulation of each individual part and the integrated one are taken to clarify the study.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1911-1916
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• 2005

In this study, the basic motor control system had been investigated. The Discrete-Time Feedback Error Learning (DTFEL) method is used to control this system. This method is anologous to the original continuous-time version Feedback Error Learning(FEL) control which is proposed as a control model of cerebellum in the field of computational neuroscience. The DTFEL controller consists of two main parts, a feedforward controller part and a feedback controller part. Each part will deals with different control problems. The feedback controller deals with robustness and stability, while the feedforward controller deals with response speed. The feedforward controller, used to solve the tracking control problem, is adaptable. To make such the tracking perfect, the adaptive law is designed so that the feedforward controller becomes an inverse system of the controlled plant. The novelty of FEL method lies in its use of feedback error as a teaching signal for learning the inverse model. The PD control theory is selected to be applied in the feedback part to guarantee the stability and solve the robust stabilization problems. The simulation of each individual part and the integrated one are taken to clarify the study.

• English Language & Literature Teaching
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• v.13 no.1
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• pp.111-131
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• 2007

This study explores teacher's corrective feedback types in an error treatment sequence in Korean EFL classroom setting. Corrective feedback moves are coded as explicit correction, recast, or initiations to self-repair. The frequency and distribution of each corrective feedback type are examined. But the special focus was given on feedback types eliciting learner's self-repair (clarification request, metalinguistic feedback, elicitation, and repetition of error) because initiations to self-repair are believed to facilitate language learning more than other strategies. The results of the study are as follows. First, there was an overwhelming tendency for teacher to use recasts whereas initiations to self-repair were not used as much as recast (52.4% vs. 29.5%). Second, the teacher tended to select feedback types in accordance with error types: namely, recasts after phonological, lexical, and translation errors and initiations to self-repair after grammatical errors though the differences were not significant. Finally, teacher's belief and students' expectation on corrective feedback were compared with actual corrective feedback representations respectively and some mismatches were found. Though both teacher and the students acknowledged the importance and necessity of self-repair, self-repair were not put into practice as such. Therefore, this study suggests more initiations to self-repair be used for effective language learning.