• 제목/요약/키워드: Output Coding

검색결과 274건 처리시간 0.028초

DSP Performance Maximization with Multisample Technique

  • Lee, Hosun;Lawrence K.W. Law;Youngyearl Han
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2000년도 제13회 신호처리 합동 학술대회 논문집
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    • pp.471-474
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    • 2000
  • In this paper, we present multisample DSP coding technique for StarCore, SC 140 DSP. The multisample programming is a pipelining technique that exploits operand reuse both coefficients and variables within kernel. A coefficient or operand is loaded once from memory and then the value may be used by multiple ALUs. It is possible to evaluate one intermediate product from each of four output sample calculations in parallel . Therefore, parallelization has been achieved by processing multiple samples in parallel rather than multiple intermediate products belonging to only one sample. The benefits of decreasing the number of memory moves per sample is to increase the algorithm perforomance. In this paper, the multisample technique has been implemented in FIR filter calculation using Motorola StarCore DSP development tool.

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A Neuro-Fuzzy Approach to Integration and Control of Industrial Processes:Part I

  • 김성신
    • 한국지능시스템학회논문지
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    • 제8권6호
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    • pp.58-69
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    • 1998
  • This paper introduces a novel neuro-fuzzy system based on the polynomial fuzzy neural network(PFNN) architecture. The PFNN consists of a set of if-then rules with appropriate membership functions whose parameters are optimized via a hybrid genetic algorithm. A polynomial neural network is employed in the defuzzification scheme to improve output performance and to select appropriate rules. A performance criterion for model selection, based on the Group Method of DAta Handling is defined to overcome the overfitting problem in the modeling procedure. The hybrid genetic optimization method, which combines a genetic algorithm and the Simplex method, is developed to increase performance even if the length of a chromosome is reduced. A novel coding scheme is presented to describe fuzzy systems for a dynamic search rang in th GA. For a performance assessment of the PFNN inference system, three well-known problems are used for comparison with other methods. The results of these comparisons show that the PFNN inference system outperforms the other methods while it exhibits exceptional robustness characteristics.

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4G networks의 멀티미디어 멀티캐스트 서비스에서 PSNR기반의 효율적인 Resource allocation (PSNR based adaptive Resource allocation for multimedia multicast service over 4G networks)

  • 김준오;권용일;서덕영
    • 한국방송∙미디어공학회:학술대회논문집
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    • 한국방송공학회 2011년도 하계학술대회
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    • pp.102-104
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    • 2011
  • 최근 비디오 스트리밍과 대화형 비디오 서비스 등과 같은 광대역 멀티미디어 서비스를 지원하기 위하여 Wimax와 같은 4G 무선네트워크 시스템 기술이 발전해 왔다. 4G 무선네트워크의 OFDM(Orthogonal Frequency Division Multiplexing)과 MIMO(multi Input Multi Output)은 사용자들에게 매우 유연한 QoS(Quality of Service) 서비스를 제공해 줄 수 있다.[1] 이 논문에서는 다양한 네트워크 상황에서 멀티캐스트 그룹에게 효율적인 방법으로 통신 자원을 할당하기 위해 OFDM 방법을 사용 하였다. 이에 본 논문에서는 한 셀(cell) 내의 서로 다른 멀티캐스트의 그룹의 다른 SNR(Signal to noise Ratio)의 사용자 분포에 따른 적응적인 scalable 비디오 멀티캐스트 방식을 제안한다. 더 나은 수신율을 가진 사용자는 최적의 MCS(Modulation and Coding Scheme) 할당을 통해 서로 다른 화질의 scalable 비디오 계층 중 높은 해상도의 비디오를 받을 수 있다. 논문에서는 전체 전송률을 최적화 하는 대신 전송받은 전체 비디오의 평균 화질을 최적화하는 방법을 제안한다.

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크레인 제어를 위한 적응 퍼지 제어기의 설계 (Design of Adaptive Fuzzy Logic Controller for Crane System)

  • 이종혁;정희명;박준호;이화석;황기현;문경준
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2005년도 제36회 하계학술대회 논문집 D
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    • pp.2714-2716
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    • 2005
  • In this paper, we designed the adaptive fuzzy logic controller for crane system using neural network and real-coding genetic algorithm. The proposed algorithm show a good performance on convergence velocity and diversity of population among evolutionary computations. The weights of neural network is adaptively changed to tune the input/output gain of fuzzy logic controller. And the genetic algorithm was used to leam the feedforward neural network. As a result of computer simulation, the proposed adaptive fuzzy logic controller is superior to conventional controllers in moving and modifying the destination point.

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고속 전력선통신 시스템의 터보 부호화 (Turbo Coded OFDM Scheme for a High-Speed Power Line Communication)

  • 이재선;김요철;김정휘;김진영
    • 한국정보통신설비학회:학술대회논문집
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    • 한국정보통신설비학회 2009년도 정보통신설비 학술대회
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    • pp.190-196
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    • 2009
  • In this paper, performance of a turbo-coded OFDM system is analyzed and simulated in a power line communication channel. Since the power line communication system typically operates in a hostile environment, turbo code has been employed to enhance reliability of transmitted data. The performance is evaluated in terms of bit error probability. As turbo decoding algorithms, MAP (maximum a posteriori), Max-Log-MAP, and SOVA (soft decision Viterbi output) algorithms are chosen and their performances are compared. From simulation results, it is demonstrated that Max-Log-MAP algorithm is promising in terms of performance and complexity. It is shown that performance is substantially improved by increasing the number of iterations and interleaver length of a turbo encoder. The results in this paper can be applied to OFDM-based high-speed power line communication systems.

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mGA의 혼합된 구조를 사용한 퍼지모델 동정 (Fuzzy Model Identification Using A mGA Hybrid Scheme)

  • 이연우;주영훈;박진배
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1999년도 하계학술대회 논문집 B
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    • pp.507-509
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    • 1999
  • In this paper, we propose a new fuzzy model identification method that can yield a successful fuzzy rule base for fundamental approximations. The method in this paper uses a set of input-output data and is based on a hybrid messy genetic algorithm (mGA) with a fine-tuning scheme. The mGA processes variable-length strings, while standard GAs work with a fixed-length coding scheme. For successfully identifying a complex nonlinear system, we first use the mGA, which coarsely optimizes the structure and the parameters of the fuzzy inference system, and then the gradient descent method which tine tunes the identified fuzzy model. In order to demonstrate the superiority and efficiency of the proposed scheme, we finally show its application to a nonlinear approximation.

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SEED 암호알고리즘의 Verilog HDL 구현을 위한 최적화 회로구조 (An Optimal Circuit Structure for Implementing SEED Cipher Algorithm with Verilog HDL)

  • 이행우
    • 디지털산업정보학회논문지
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    • 제8권1호
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    • pp.107-115
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    • 2012
  • This paper proposes on the structure for reducing the circuit area and increasing the computation speed in implementing to hardware using the SEED algorithm of a 128-bit block cipher. SEED cipher can be implemented with S/W or H/W method. It should be important that we have minimize the area and computation time in H/W implementation. To increase the computation speed, we used the structure of the pipelined systolic array, and this structure is a simple thing without including any buffer at the input and output circuit. This circuit can record the encryption rate of 320 Mbps at 10 MHz clock. We have designed the circuit with the Verilog HDL coding showing the circuit performances in the figures and the table.

An Implementation Method of Cycle Accurate Simulator for the Design of a Pipelined DSP

  • Park, Hyeong-Bae;Park, Ju-Sung;Kim, Tae-Hoon;Chi, Hua-Jun
    • JSTS:Journal of Semiconductor Technology and Science
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    • 제6권4호
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    • pp.246-251
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    • 2006
  • In this paper, we introduce an implementation method of the CBS (Cycle Base Simulator), which describes the operation of a DSP (Digital Signal Processor) at a pipeline cycle level. The CBS is coded with C++, and is verified by comparing the results from the CBS and HDL simulation of the DSP with the various test vectors and application programs. The CBS shows the data about the internal registers, status flags, data bus, address bus, input and output pin of the DSP, and also the control signals at each pipeline cycle. The developed CBS can be used in evaluating the performance of the target DSP before the RTL(Register Transfer Level) coding as well as a reference for the RTL level design.

기호 코딩을 이용한 유전자 알고리즘 기반 퍼지 다항식 뉴럴네트워크의 설계 (Design of Genetic Algorithms-based Fuzzy Polynomial Neural Networks Using Symbolic Encoding)

  • 이인태;오성권;최정내
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2006년도 심포지엄 논문집 정보 및 제어부문
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    • pp.270-272
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    • 2006
  • In this paper, we discuss optimal design of Fuzzy Polynomial Neural Networks by means of Genetic Algorithms(GAs) using symbolic coding for non-linear data. One of the major subject of genetic algorithms is representation of chromosomes. The proposed model optimized by the means genetic algorithms which used symbolic code to represent chromosomes. The proposed gFPNN used a triangle and a Gaussian-like membership function in premise part of rules and design the consequent structure by constant and regression polynomial (linear, quadratic and modified quadratic) function between input and output variables. The performance of the proposed model is quantified through experimentation that exploits standard data already used in fuzzy modeling. These results reveal superiority of the proposed networks over the existing fuzzy and neural models.

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Low-Complexity Maximum-Likelihood Decoder for VBLAST-STBC Scheme Using Non-square OSTBC Code Rate 3/4

  • Pham Van-Su;Le Minh-Tuan;Mai Linh;Yoon Gi-Wan
    • Journal of information and communication convergence engineering
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    • 제4권2호
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    • pp.75-78
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    • 2006
  • This work presents a low complexity maximum-likelihood decoder for signal detection in VBLAST-STBC system, which employs non-square O-STBC code rate 3/4. Stacking received symbols from different symbol duration and applying QR decomposition result in the special format of upper triangular matrix R so that the proposed decoder is able to provide not only ML-like BER performance but also very low computational load. The low computational load and ML-like BER performance properties of the proposed decoder are verified by computer simulations.