• Title/Summary/Keyword: Vector Generation

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Bidding Strategy Determination by Defining Strategy Vector (전략벡터정의를 통한 입찰전략수립)

  • Kang, Dong-Joo;Moon, Young-Hwan;Oh, Tae-Kyoo;Kim, Bal-Ho
    • Proceedings of the KIEE Conference
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    • 2001.11b
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    • pp.60-62
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    • 2001
  • This paper shows the optimal bidding strategy determination method using Nash equilibrium concept by defining bidding strategy vector. This vector is 2-dimension vector whose components are generation amount and generation cost. Thereby we are able to make all possible strategies and their's payoff table. And then we erase dominated strategies one by one so that we obtain Nash equilibrium, the optimal bidding strategy of generation bidding game.

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A study on the application of residual vector quantization for vector quantized-variational autoencoder-based foley sound generation model (벡터 양자화 변분 오토인코더 기반의 폴리 음향 생성 모델을 위한 잔여 벡터 양자화 적용 연구)

  • Seokjin Lee
    • The Journal of the Acoustical Society of Korea
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    • v.43 no.2
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    • pp.243-252
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    • 2024
  • Among the Foley sound generation models that have recently begun to be studied, a sound generation technique using the Vector Quantized-Variational AutoEncoder (VQ-VAE) structure and generation model such as Pixelsnail are one of the important research subjects. On the other hand, in the field of deep learning-based acoustic signal compression, residual vector quantization technology is reported to be more suitable than the conventional VQ-VAE structure. Therefore, in this paper, we aim to study whether residual vector quantization technology can be effectively applied to the Foley sound generation. In order to tackle the problem, this paper applies the residual vector quantization technique to the conventional VQ-VAE-based Foley sound generation model, and in particular, derives a model that is compatible with the existing models such as Pixelsnail and does not increase computational resource consumption. In order to evaluate the model, an experiment was conducted using DCASE2023 Task7 data. The results show that the proposed model enhances about 0.3 of the Fréchet audio distance. Unfortunately, the performance enhancement was limited, which is believed to be due to the decrease in the resolution of time-frequency domains in order to do not increase consumption of the computational resources.

Photonic Generation of Frequency-tripling Vector Signal Based on Balanced Detection without Precoding or Optical Filter

  • Qu, Kun;Zhao, Shanghong;Li, Xuan;Zhu, Zihang;Tan, Qinggui
    • Current Optics and Photonics
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    • v.2 no.2
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    • pp.134-139
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    • 2018
  • A novel approach for frequency-tripling vector signal generation via balanced detection without precoding and optical filter is proposed. The scheme is mainly utilizing an integrated dual-polarization quadrature phase shift keying (DPQPSK) modulator. In the DPQPSK modulator, one QPSK modulator is driven by an RF signal to generate high-order optical sidebands, while the other QPSK modulator is modulated by I/Q data streams to produce baseband vector signal as an optical carrier. After that, a frequency-tripling 16-quadrature-amplitude-modulation (16QAM) vector millimeter-wave (mm-wave) signal can be obtained by balanced detection. The proposed scheme can reduce the complexity of transmitter digital signal processing. The results show that, a 4 Gbaud baseband 16QAM vector signal can be generated at 30 GHz by frequency-tripling. After 10 km single-mode fiber (SMF) transmission, the constellation and eye diagrams of the generated vector signal perform well and a bit-error-rate (BER) below than 1e-3 can be achieved.

A Feature Vector Generation Technique through Gradient Correction of an Outline in the Mouth Region (입 영역에서 외곽선의 기울기 보정을 통한 특징벡터 생성 기법)

  • Park, Jung Hwan;Jung, Jong Jin;Kim, Guk Boh
    • Journal of Korea Multimedia Society
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    • v.17 no.10
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    • pp.1141-1149
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    • 2014
  • Recently, various methods to effectively eliminate the noise are researched in image processing techniques. However, the conventional noise filtering techniques, which remove most of the noise, are less efficient for remained noise detection after filtering due to exploiting no face feature information. In this paper, we proposed a feature vector generation technique in the mouth region by distinguishing and revising the remained noise through gradient correction, when the outline is extracted after performing noise filtering.

Feasible Power Loss Analysis and Estimation of Auxiliary Resonant DC Link Assisted Soft-Switching Inverter with New Zero Vector Generation Method

  • Manabu Kurokawa;Claudio Y. Inaba;M. Rukonuzzaman;Eiji Hiraki;Yoshihiro Konishi;Mutsuo Nakaoka
    • Journal of Power Electronics
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    • v.2 no.2
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    • pp.77-87
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    • 2002
  • The purpose of this paper is to improve power conversion efficiency of three-phase soft-switching voltage-source inverter with an auxiliary resonant dc link (ARDCL) snubber circuit. Firstly, the operation principle of ARDCL snubber circuit is described. Secondly, this paper proposes an effictive generation method of zero voltage vector for three-phase voltage-source soft-switching inverter in power losses in which power losses in the ARDCL snubber circuit can be reduced. In particular, zero voltage holding interval in the inverter DC busline can be controlled due to the new generation scheme of zero voltage vector. Thirdly, a simulator for power loss analysis for power loss characteristics based on actual system, is developed. the validity of developed. The validity of developed simulator of proved with experimental results. Finally, power efficency of three-phase inverter is estimated according to high carrier frequency by using the simulatior.

An Efficient Vector Quantization Codebook generation using a Triangle Inequality (삼각 부등식을 이용한 빠른 벡터 양자화 코드북 생성)

  • Lee, Hyun-Jin
    • Journal of Digital Contents Society
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    • v.13 no.3
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    • pp.309-315
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    • 2012
  • Active data are the input data which are changed its membership as Vector Quantization codebook generation algorithm is processed. In the process of VQ codebook generation algorithm performed, the actual active data out of the entire input data will be less presented as the process is performed. Therefore, if we can accurately find the active data and only if we are going to do VQ codebook generation on the active data, then we can significantly reduce the overall generation time. In this paper, we presented the triangle inequality based algorithm to select the active data. Experimental results show that our algorithm is superior to other methods in terms of the VQ codebook generation time.

High Level Test Generation (상위 수준 설계에서의 테스트패턴 생성)

  • 김종현;박승규김동욱
    • Proceedings of the IEEK Conference
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    • 1998.10a
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    • pp.1005-1008
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    • 1998
  • IC testing plays a very important role in IC manufacturing process. Modern complex ASIC chips making it difficult for gate level and RLT level test generation techniques to generate good test vector in resonable time. In this paper we proposed new test pattern generation method in VHDL description to detect manufacturing faults. This method based on software testing can easily generate test vector and independent to synthesis result.

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A Technique of Feature Vector Generation for Eye Region Using Embedded Information of Various Color Spaces (다양한 색공간 정보를 이용한 눈 영역의 특징벡터 생성 기법)

  • Park, Jung-Hwan;Shin, Pan-Seop;Kim, Guk-Boh;Jung, Jong-Jin
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.64 no.1
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    • pp.82-89
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    • 2015
  • The researches of image recognition have been processed traditionally. Especially, face recognition technology has been received attractions with advance and applied to various areas according as camera sensor embedded into many devices such as smart phone. In this study, we design and develop a feature vector generation technique of face for making animation caricatures using methods for face detection which are previous stage of face recognition. At first, we detect both face region and detailed eye region of component element by Viola&Johns's realtime detection method which are called as ROI(Region Of Interest). And then, we generate feature vectors of eye region by utilizing factors as opposed to the periphery and by using appearance information of eye. At this point, we focus on the embedded information in many color spaces to overcome the problems which can be occurred by using one color space. We propose a feature vector generation method using information from many color spaces. Finally, we experiment the test of feature vector generation by the proposed method with enough quantity of sample picture data and evaluate the proposed method for factors of estimating performance such as error rate, accuracy and generation time.

Generation of Pattern Classifiers Based on Linear Nongroup CA

  • Choi, Un-Sook;Cho, Sung-Jin;Kim, Han-Doo
    • Journal of Korea Multimedia Society
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    • v.18 no.11
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    • pp.1281-1288
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    • 2015
  • Nongroup Cellular Automata(CA) having two trees in the state transition diagram of a CA is suitable for pattern classifier which divides pattern set into two classes. Maji et al. [1] classified patterns by using multiple attractor cellular automata as a pattern classifier with dependency vector. In this paper we propose a method of generation of a pattern classifier using feature vector which is the extension of dependency vector. In addition, we propose methods for finding nonreachable states in the 0-tree of the state transition diagram of TPMACA corresponding to the given feature vector for the analysis of the state transition behavior of the generated pattern classifier.

Low Sit Rate Image Coding using Neural Network (신경망을 이용한 저비트율 영상코딩)

  • 정연길;최승규;배철수
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2001.10a
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    • pp.579-582
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    • 2001
  • Vector Transformation is a new method unified vector quantization and coding. So far, codebook generation applied to coding was LBG algorithm. But using the advantage of SOFM(Self-Organizing Feature Map) based on neural network can improve a system's performance. In this paper, we generated VTC(Vector Transformation Coding) codebook applied with SOFM algorithm and compare the result for several coding rates with LBG algorithm. The problem of Vector quantization is complicated calculation and codebook generation. So, to solve this problem, we used neural network approach method.

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