• Journal of Information Processing Systems
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• v.16 no.1
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• pp.145-154
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• 2020

Maximum likelihood (ML) is the best estimator asymptotically as the number of training samples approaches infinity. This paper deduces an adaptive algorithm for blind signal processing problem based on gradient optimization criterion. A parametric density model is introduced through a parameterized generalized distribution family in ML framework. After specifying a limited number of parameters, the density of specific original signal can be approximated automatically by the constructed density function. Consequently, signal separation can be conducted without any prior information about the probability density of the desired original signal. Simulations on classical biomedical signals confirm the performance of the deduced technique.

• Proceedings of the IEEK Conference
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• 2001.06a
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• pp.69-72
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• 2001

Blind equalization of transmission channel is important in communication areas and signal processing applications because it does not need training sequence, nor does it require a priori channel information. Recently, Tong et al. proposed solutions for this problem exploit the diversity induced by antenna array or time oversampling, leading to the second order statistics techniques, fur example, subspace method, prediction error method, and so on. The linear prediction error method is perhaps the most attractive in practice due to the insensitive to blind equalizer length mismatch as well as for its simple adaptive filter implementation. Unfortunately, the previous one-step prediction error method is known to be limited in arbitrary delay. In this paper, we induce the optimal delay, and propose the adaptive blind equalizer with multi-step linear prediction using RLS-type algorithm. Simulation results are presented to demonstrate the proposed algorithm and to compare it with existing algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.8A
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• pp.753-762
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• 2002

Blind equalization of transmission channel is important in communication areas and signal processing applications because it does not need training sequences, nor dose it require a priori channel information. In this paper, an adaptive blind MMSE channel equalization technique based on second-order statistics in investigated. We present an adaptive blind MMSE channel equalization using multichannel linear prediction error method for estimating cross-correlation vector. They can be implemented as RLS or LMS algorithms to recursively update the cross-correlation vector. Once cross-correlation vector is available, it can be used for MMSE channel equalization. Unlike many known subspace methods, our proposed algorithms do not require channel order estimation. Therefore, our algorithms are robust to channel order mismatch. Performance of our algorithms and comparisons with existing algorithms are shown for real measured digital microwave channel.

• Journal of Information Processing Systems
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• v.13 no.2
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• pp.385-399
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• 2017

Nowadays, with the development of signal processing technique, the protection to the integrity and authenticity of images has become a topic of great concern. A blind image authentication technology with high tamper detection accuracy for different common attacks is urgently needed. In this paper, an improved fragile watermarking method based on local binary pattern (LBP) is presented for blind tamper location in images. In this method, a binary watermark is generated by LBP operator which is often utilized in face identification and texture analysis. In order to guarantee the safety of the proposed algorithm, Arnold transform and logistic map are used to scramble the authentication watermark. Then, the least significant bits (LSBs) of original pixels are substituted by the encrypted watermark. Since the authentication data is constructed from the image itself, no original image is needed in tamper detection. The LBP map of watermarked image is compared to the extracted authentication data to determine whether it is tampered or not. In comparison with other state-of-the-art schemes, various experiments prove that the proposed algorithm achieves better performance in forgery detection and location for baleful attacks.

• Journal of Information Processing Systems
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• v.2 no.1
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• pp.13-17
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• 2006

In this paper, we propose an audio extraction method to decrease the influence of the original signal by modifying the watermarking detection system proposed by P. Bassia et al. In the extraction of the watermark, we employ a simple mean filter to remove the influence of the original signal as a preprocessing of extraction and the repetitive insertion of the watermark. As the result of the experiment, for which we used about 20 kinds of actual audio data, we obtain a watermark detection rate of about 95% and a good performance even after the various signal processing attacks.

• The KIPS Transactions:PartD
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• v.16D no.2
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• pp.249-256
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• 2009

This paper introduces an efficient USN (ubiquitous sensor network) for monitoring blind areas in a skiing resort, developed as a part of u-Sport showcase project of Gangwon Province. Blind areas of a skiing resort are dangerous and/or steep areas located aroud ski slopes, which are rarely traveled and not easily seen by a ski patrol. If an accident occurs in such a blind area, the main control center of the sking resort can hardly recognize the accident and provide first aid and rescue services promptly. The blind area monitoring system proposed in this paper monitors a blind area of a skiing resort using five battery-powered sensor nodes each of which has an image sensor on it and wirelessly transmits images around the blind area to the main control center on a regular basis, therebly allowing real-time monitoring of the blind area and prompt rescue services in case of accidents. Additionally, the monitoring system provides an emergency button which skiers injured in the blind area can push. If the button is pushed, an image around the button and an alarm signal are transmitted to the main control center and therefore the main control center can take prompt actions for rescuing the injured skiers.

• Proceedings of the Korean Society of Computer Information Conference
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• 2014.01a
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• pp.89-92
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• 2014

This paper presents a secure and blind adaptive audio watermarking algorithm based on Empirical Mode Decomposition (EMD). The audio signal is divided into frames and each one is decomposed adaptively, by EMD, into several Intrinsic Mode Functions (IMFs). The watermark and the synchronization codes are then embedded into the extrema of the last IMF. The experimental results show that the proposed method has good imperceptibility and robustness against signal processing attacks.

• Journal of Broadcast Engineering
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• v.9 no.2
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• pp.110-118
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• 2004

This paper shows that blind deconvolution has only finite solutions when an original image and a point spread function are nonzero over a restricted domain, in other words, an observed image has a compact support. The key of the proof is to use z-transformations and factorizations of polynomials. Then, we propose an algorithm to find all finite solutions under the boundary condition. Finally, we confirm that we can extract all sets of an original image and a point spread function from a degraded image by using our algorithm in numerical examples.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.953-955
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• 2014

최근 차량 충돌 방지를 위한 다양한 기술이 상용화되고 있다. FMCW 기반의 레이더 시스템은 구현의 용이성으로 많은 상용차에서 전면 충돌 방지 시스템에 적용되고 있다. 측면 충돌 방지를 위한 BSD(Blind Spot Detection)와 차선변경 보조 시스템(LCA, Lane Change Assistant system)에서는 전방 레이더보다 인식거리가 줄어들고 갱신율이 낮아지므로 고속 FFT 등을 수행하는 신호처리부를 저가격으로 설계가 가능할 것이다. 본 연구에서는 TI사의 MCU인 F28335를 사용하여 근거리를 인식하는 신호처리부를 설계하였다. 이 MCU는 16채널 12bit ADC와 68KB RAM 및 512KB 플래시 메모리를 내장하고, 150MHz 부동소수점 연산을 지원하여 단일 칩으로 신호처리부의 구현이 가능하다. 구현된 시스템은 20m내외의 거리에 있는 장애물에 대하여 10Hz로 갱신이 가능하여 BSD를 위한 기본 기능이 확인되었다. 이러한 구현은 이전의 고가의 DSP나 FPGA를 사용하지 않고 15$이내의 단일 MCU와 간단한 아날로그 회로로 설계되어 저가격의 시스템으로 상용화가 가능할 것이다.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.261-263
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• 2006

Nowadays, technologies such as RFID, sensor network makes our life comfortable more and more. In this paper we propose a wearable computing system for blind and deaf person who can be easily out of sight from our technology. We are making a wearable computing system that is consisted of embedded board to processing data, ultrasonic sensors to get distance data and motors that make vibration as a signal to see the screen for a deaf person. This system offers environmental informations by text and voice. For example, distance data from a obstacle to a person are calculated by data compounding module using sensed ultrasonic reflection time. This data is converted to text or voice by main processing module, and are serviced to a handicapped person. Furthermore we will extend this system using a voice recognition module and text to voice convertor module to help communication among the blind and deaf persons.