• Journal of Communications and Networks
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• v.9 no.2
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• pp.118-127
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• 2007

We propose a link adaptation and selection method for the links constituting an orthogonal frequency division multiplexing (OFDM) based wireless relay network. The proposed link adaptation and selection method selects the forwarding, modulation, and channel coding schemes providing the highest end-to-end throughput and decides whether to use the relay or not. The link adaptation and selection is done for each sub-channel based on instantaneous signal to interference plus noise ratio (SINR) conditions in the source-to-destination, source-to-relay and relay-to-destination links. The considered forwarding schemes are amplify and forward (AF) and simple adaptive decode and forward (DF). Efficient adaptive modulation and coding decision rules are provided for various relaying schemes. The proposed end-to-end link adaptation and selection method ensures that the end-to-end throughput is always larger than or equal to that of transmissions without relay and non-adaptive relayed transmissions. Our evaluations show that over the region where relaying improves the end-to-end throughput, the DF scheme provides significant throughput gain over the AF scheme provided that the error propagation is avoided via error detection techniques. We provide a frame structure to enable the proposed link adaptation and selection method for orthogonal frequency division multiple access (OFDMA)-time division duplex relay networks based on the IEEE 802.16e standard.

• Journal of Broadcast Engineering
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• v.16 no.5
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• pp.797-800
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• 2011

The objective of MPEG Media Transport (MMT), which is on going standard, is to develop efficient delivery of media over packet based networks in an adaptive, progressive, download/streaming fashion over various IP based networks, including terrestrial, satellite and cable broadcast networks. In this paper we introduce utilization of signal strength information based on Cross Layer Design(CLD) to efficient multimedia delivery over wireless network in which in practice the wireless conditions can vary significantly. Many recent studies have shown that a significant improvement in wireless video throughput can be achieved by utilizing signal strength information on CLD [1][2]. Despite of its usefulness, however, it was difficult to employ signal strength information in rate adaptation applications due to different representation of signal strength information for each underlying wireless network. To that end, we proposed syntax and semantics of signal strength information in such a way that the information can be interpreted in the unified way. The proposed signal strength information was proposed for the MMT standardization.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.3
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• pp.21-26
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• 2002

This paper presents the new approach of identifying human emotional states such as anger, happiness, normal, sadness, or surprise. This is accomplished by using discrete duration continuous hidden Markov models(DDCHMM). For this, the emotional feature parameters are first defined from input speech signals. In this study, we used prosodic parameters such as pitch signals, energy, and their each derivative, which were then trained by HMM for recognition. Speaker adapted emotional models based on maximum a posteriori(MAP) estimation were also considered for speaker adaptation. As results, the simulation performance showed that the recognition rates of vocal emotion gradually increased with an increase of adaptation sample number.

• Proceedings of the IEEK Conference
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• 2002.06e
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• pp.39-42
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• 2002

A new adaptive PRML architecture, considered not only DVD-ROM but also DVD-Multi including DVD-RAM as well, is presented to demonstrate its superiority over the conventional analog channel in a DVD system. For this new architecture, channel adaptation algorithm using gain controlled type of FIR filter, and asymmetry compensation algorithm using expected level adaptation of viterbi decoder are presented. In addition, a method of modelling the disk tilt and asymmetrical read-back signal are discussed.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.10
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• pp.1488-1497
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• 1989

In this paper, a new adaptive control scheme is proposed that uses a special form of rational function-type linear operator in the parameter adaptation and that removes the augmenting signal terms of the control input components. This adaptation scheme is applied to the MRAC of continuous-time, linear time-invariant, minimum-phase plants whose relative degrees are arbitrary. This scheme can be applied without any change of the controller structure to the adaptive systems regardless of the relative degree if it is greater than 1. And this scheme does not require any signal augmentation for arbitrary relative-degree plants if the reference model has no zeros. The asymptotic stability of the adaptive systems controlled by this scheme is shown by a hyper-stability method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.2
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• pp.445-451
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• 2010

This paper presents a threshold adaptation based voice query transcription scheme for music information retrieval. The proposed scheme analyzes monophonic voice signal and generates its transcription for diverse music retrieval applications. For accurate transcription, we propose several advanced features including (i) Energetic Feature eXtractor (EFX) for onset, peak, and transient area detection; (ii) Modified Windowed Average Energy (MWAE) for defining multiple small but coherent windows with local threshold values as offset detector; and finally (iii) Circular Average Magnitude Difference Function (CAMDF) for accurate acquisition of fundamental frequency (F0) of each frame. In order to evaluate the performance of our proposed scheme, we implemented a prototype music transcription system called AMT2 (Automatic Music Transcriber version 2) and carried out various experiments. In the experiment, we used QBSH corpus [1], adapted in MIREX 2006 contest data set. Experimental result shows that our proposed scheme can improve the transcription performance.

• Journal of Biomedical Engineering Research
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• v.29 no.1
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• pp.25-31
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• 2008

It is well known that temporal information, i.e speech onset, about input speech can be represented to the response nerve signal of auditory nerve better depending on the adaptation effect occurred in the auditory nerve synapse. In addition, the performance of a speech processor of cochlear implant can be improved by the adaptation effect. In this paper, we observed the emphasis characteristic of speech onset in the recently proposed adaptation algorithm, analyzed the characteristic of performance change according to the variation of parameters and compared with transient emphasis spectral maxima (TESM) is the previous typical strategy. When observing false peaks which are generated everywhere except speech onset, in the case of the proposed model, the false peak were generated much less than in the case of the TESM and it is more distinguishable under noise.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.10a
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• pp.86-91
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• 2004

It is very important to detect the bearing defects in rotating machinery since the critical failure of bearing cause a machinery shutdown. However it is difficult to detect the vibration signal resulting from the initial defects of bearing because of the high level of broadband noise. A signal processing technique, called the adaptive line enhancer(ALE) as one of adaptive filter, is studied in this work. This technique is to eliminate broadband noise without a prior knowledge of the noise and signal characteristics. Also we propose the optimal methods for selecting the three main ALE parameters such as correlation length, filter order and adaptation constant used in the adaptative process. Vibration signals for three abnormal bearings, including inner and outer raceways and ball defects, were acquired from Anderon(angular derivative of radius on)meter. The experimental results showed that the proposed technique can reliably detect the bearing defective signals masked by broadband noise.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.1
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• pp.138-149
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• 1994

This paper introduces a new monitoring technique which utilizes an adaptive signal processing for feature generation, coupled with a multilayered merual network for pattern recognition. The cutting force signal in face milling operation was modeled by a low order discrete autoregressive model, shere parameters were estimated recursively at each sampling instant using a parameter adaptation algorithm based on an RLS(recursive least square) method with discounted measurements. The influences of the adaptation algorithm parameters as well as some considerations for modeling on the estimation results are discussed. The sensitivity of the extimated model parameters to the tool state(new and worn tool)is presented, and the application of a multilayered neural network to tool state monitoring using the previously generated features is also demonstrated with a high success rate. The methodology turned out to be quite suitable for in-process tool wear monitoring in the sense that the model parameters are effective as tool state features in milling operation and that the classifier successfully maps the sensors data to correct output decision.

• Journal of Convergence for Information Technology
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• v.10 no.5
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• pp.1-7
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• 2020

This paper proposes a link adaptation method for Underwater Internet of Things (IoT), which reduces power consumption of sensor nodes and improves the throughput of network in underwater IoT network. Adaptive Modulation and Coding (AMC) technique is one of link adaptation methods. AMC uses the strong correlation between Signal Noise Rate (SNR) and Bit Error Rate (BER), but it is difficult to apply in underwater IoT as it is. Therefore, we propose the machine learning based AMC technique for underwater environments. The proposed Modulation Coding and Scheme (MCS) prediction model predicts transmission method to achieve target BER value in underwater channel environment. It is realistically difficult to apply the predicted transmission method in real underwater communication in reality. Thus, this paper uses the high accuracy BER prediction model to measure the performance of MCS prediction model. Consequently, the proposed AMC technique confirmed the applicability of machine learning by increase the probability of communication success.