• Title/Summary/Keyword: Information input algorithm

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A Source Separation Algorithm for Stereo Panning Sources (스테레오 패닝 음원을 위한 음원 분리 알고리즘)

  • Baek, Yong-Hyun;Park, Young-Cheol
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.4 no.2
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    • pp.77-82
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    • 2011
  • In this paper, we investigate source separation algorithms for stereo audio mixed using amplitude panning method. This source separation algorithms can be used in various applications such as up-mixing, speech enhancement, and high quality sound source separation. The methods in this paper estimate the panning angles of individual signals using the principal component analysis being applied in time-frequency tiles of the input signal and independently extract each signal through directional filtering. Performances of the methods were evaluated through computer simulations.

Simple Cell Scheduling Algorithm for Input and Output Buffered ATM Switch (입출력 버퍼형 ATM 스위치의 단순 셀 스케줄링 알고리즘)

  • Han, Man-Soo;Han, In-Tak;Lee, Beom-Cheol
    • Annual Conference of KIPS
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    • 2000.10b
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    • pp.1099-1102
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    • 2000
  • 입출력버퍼형 스위치를 위한 간단한 셀 스케줄링 알고리즘을 제시한다. 스위치는 고속동작 및 성능 향상을 위해 이중 스위칭 플랜을 갖고 있다. 제안한 알고리즘은 각각의 스위칭 플랜에서 독립적으로 수행되며 전송요청 (request), 전송허가(grant). 전송확정 (accept)의 3 단계 동작으로 이루어져 있다. 또한 각 3 단계동작을 한 셀시간에 한 번씩만 수행하여 단위 셀시간이 작은 고속 스위칭에 적합하다. 모의실험 결과 제안한 알고리즘의 성능이 Bernoulli 트래픽 입력에 대해 출력버퍼형 스위치의 성능과 거의 동일하였다.

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The Transformation Time-invarying Linear System for a Class of Time-varying Linear System via I/O Transformation (입출력 변환을 이용한 선형 시변 시스템의 선형 시불변 변환)

  • Cho, Do-Hyoun;Won, Young-Jin;Cho, Chang-Ho;Lee, Tae-Sick;Lee, Jong-Yong
    • Proceedings of the IEEK Conference
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    • 2007.07a
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    • pp.483-484
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    • 2007
  • In this paper, we consider the input-output transformation for the time-varying linear system and get the time-invarying linear system. And we present the necessary sufficient condition for the I/O transformation. The transformed system represent the system with the multiple integral. We verify the proposal algorithm via the example and examine.

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Guitar Tab Digit Recognition and Play using Prototype based Classification

  • Baek, Byung-Hyun;Lee, Hyun-Jong;Hwang, Doosung
    • Journal of the Korea Society of Computer and Information
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    • v.21 no.9
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    • pp.19-25
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    • 2016
  • This paper is to recognize and play tab chords from guitar musical sheets. The musical chord area of an input image is segmented by changing the image in saturation and applying the Grabcut algorithm. Based on a template matching, our approach detects tab starting sections on a segmented musical area. The virtual block method is introduced to search blanks over chord lines and extract tab fret segments, which doesn't cause the computation loss to remove tab lines. In the experimental tests, the prototype based classification outperforms Bayesian method and the nearest neighbor rule with the whole set of training data and its performance is similar to that of the support vector machine. The experimental result shows that the prediction rate is about 99.0% and the number of selected prototypes is below 3.0%.

Classification of Interval Vectors by Interval Neural Networks (구간 신경망에 의한 구간 벡터의 식별)

  • 권기택
    • Journal of Korea Society of Industrial Information Systems
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    • v.6 no.2
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    • pp.1-6
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    • 2001
  • This paper proposes a pattern classification method of interval vectors by interval neural networks. The proposed method can be applied to pattern classification where attribute values of each sample are given as interval numbers. First, an architecture of interval neural networks is proposed for dealing with interval input vectors. Next, a learning algorithm is derived from the cost function. a cost function is defined using the interval output from the interval neural network and the corresponding target output. Last, using numerical examples, the proposed approach is illustrated and compared with other approach based on the standard back-propagation neural networks.

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On Factorizing the Discrete Cosine Transform Matrix (DCT 행렬 분해에 관한 연구)

  • 최태영
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.16 no.12
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    • pp.1236-1248
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    • 1991
  • A new fast algorithm for computing the discrete cosine transform(DCT) Is developed decomposing N-point DCT into an N /2-point DCT and two N /4 point transforms(transpose of an N /4-point DCT. TN/t'and)It has an important characteristic that in this method, the roundoff noise power for a fixed point arithmetic can be reduced significantly with respect to the wellknown fast algorithms of Lee and Chen. since most coefficients for multiplication are distributed at the nodes close to the output and far from the input in the signal flow graph In addition, it also shows three other versions of factorization of DCT matrix with the same number of operations but with the different distributions of multiplication coefficients.

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Adaptive DC to AC Invertor Design based on Fuzzy Inference for Power Consumption monitoring (퍼지 추론을 이용한 적응적 DC/AC 인버터 설계)

  • 김윤호
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.7 no.7
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    • pp.1520-1526
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    • 2003
  • Design and implementation method or the 100[W] DD/AC invertor using PICl6C711 processor is described in this paper. Especially, fuzzy inference algorithm is involved in this system which can be adaptive to the environment variation. Input/output control and power consumption monitoring is controlled based on PIC16C711 processor, which compute the optimal values acquired from inference engine. Such experimental as function, efficiency, motoring are performed and experimental results showed that monitoring error is less than 2% and widely used in the area of industrial fields.

A study on pattern recognition using DCT and neural network (DCT와 신경회로망을 이용한 패턴인식에 관한 연구)

  • 이명길;이주신
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.22 no.3
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    • pp.481-492
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    • 1997
  • This paper presents an algorithm for recognizing surface mount device(SMD) IC pattern based on the error back propoagation(EBP) neural network and discrete cosine transform(DCT). In this approach, we chose such parameters as frequency, angle, translation and amplitude for the shape informantion of SMD IC, which are calculated from the coefficient matrix of DCT. These feature parameters are normalized and then used for the input vector of neural network which is capable of adapting the surroundings such as variation of illumination, arrangement of objects and translation. Learning of EBP neural network is carried out until maximum error of the output layer is less then 0.020 and consequently, after the learning of forty thousand times, the maximum error have got to this value. Experimental results show that the rate of recognition is 100% in case of the random pattern taken at a similar circumstance as well as normalized training pattern. It also show that proposed method is not only relatively relatively simple compare with the traditional space domain method in extracting the feature parameter but also able to re recognize the pattern's class, position, and existence.

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A Method for Quantitative Performance Evaluation of Edge Detection Algorithms Depending on Chosen Parameters that Influence the Performance of Edge Detection (경계선 검출 성능에 영향을 주는 변수 변화에 따른 경계선 검출 알고리듬 성능의 정량적인 평가 방법)

  • 양희성;김유호;한정현;이은석;이준호
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.25 no.6B
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    • pp.993-1001
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    • 2000
  • This research features a method that quantitatively evaluates the performance of edge detection algorithms. Contrary to conventional methods that evaluate the performance of edge detection as a function of the amount of noise added to he input image, the proposed method is capable of assessing the performance of edge detection algorithms based on chosen parameters that influence the performance of edge detection. We have proposed a quantitative measure, called average performance index, that compares the average performance of different edge detection algorithms. We have applied the method to the commonly used edge detectors, Sobel, LOG(Laplacian of Gaussian), and Canny edge detectors for noisy images that contain straight line edges and curved line edges. Two kinds of noises i.e, Gaussian and impulse noises, are used. Experimental results show that our method of quantitatively evaluating the performance of edge detection algorithms can facilitate the selection of the optimal dge detection algorithm for a given task.

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Performance Analysis of AGC Applebaum Array for Multiple Narrowband Interference (다중의 협대역 간섭 신호에 대한 AGC Applebaum어레이의 성능 분석)

  • 윤동현;이규만;한동석
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.25 no.6B
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    • pp.1092-1099
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    • 2000
  • An adaptive array system can effectively remove all received interferences by using adaptive algorithms even though the received signal condition is not known. The conventional adaptive array systems, however, cannot remove all interferences adaptively and converge very slowly when the eigenvalue spread of the input covariance matrix is large. In the paper, a new adaptive array system called an automatic gain controller (AGC) Applebaum array and its control algorithm are proposed to overcome the performance degradation of conventional Applebaum array in multiple interference conditions. The performance analysis of the proposed AGC Applebaum array is described under the condition of multiple narrowband interferences. Simulation results show the array output signal-to-noise ratio (SNR) of the AGC Applebaum array increases by 30dB compared to that of the conventional Applebaum array in the simulation condition. The gain of the AGC Applebaum array in the incident direction of a weaker interference is also shown to be lower than that of the conventional Applebaum array.

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