• Title/Summary/Keyword: signal Processing

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Audio Context Recognition Using Signal's Reconstructed Phase Space (신호의 복원된 위상 공간을 이용한 오디오 상황 인지)

  • Vinh, La The;Khattak, Asad Masood;Loan, Trinh Van;Lee, Sungyoung;Lee, Young-Ko
    • Proceedings of the Korea Information Processing Society Conference
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    • 2009.11a
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    • pp.243-244
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    • 2009
  • So far, many researches have been conducted in the area of audio based context recognition. Nevertheless, most of them are based on existing feature extraction techniques derived from linear signal processing such as Fourier transform, wavelet transform, linear prediction... Meanwhile, environmental audio signal may potentially contains non-linear dynamic properties. Therefore, it is a big potential to utilize non-linear dynamic signal processing techniques in audio based context recognition.

Neural Network Approaches and Trends for Speech Recognition (음성 인식을 위한 신경회로망 접근과 동향)

  • 김순협
    • Proceedings of the Acoustical Society of Korea Conference
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    • 1995.06a
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    • pp.33-41
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    • 1995
  • We proposed the approach method of neural network for signal processing, especially speech signal processing and reviewed the algorithms for several neural networks which are used for many alppication field in speech processing. Finally, investigated the trends in neural network method through 3 conference jounal and the ASK jounal in 1994.

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Effects Analysis of DRAM for Digital Signal Processor Performance (디지털 신호처리 프로세서의 성능에 대한 DRAM의 영향 분석)

  • Lee, Jongbok
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.18 no.3
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    • pp.177-183
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    • 2018
  • Currently, digital signal processing systems are used extensively in image processing, audio processing, filtering, and equalizations, etc. In addition, the importance of DRAM, which has a great influence on the performance of an digital signal processor has been increased, making research on DRAM actively conducted in industry and academia. Therefore, it is important to have a more accurate DRAM model in order to obtain reliable results when evaluating the performance of a digital signal processor through simulation. In this paper, we developed a digital signal processor simulator capable of inter-working with a DRAM simulator. With the simulator, we analyzed the influence of the DRAM model which operates correctly on a cycle-by-cycle basis, on the performance of the digital signal processor by using the UTDSP digital signal benchmark.

English Digital Signal Processing Circuit in HD Monitor using Synchronization Signal Optimization (동기신호 최적화 기법을 통한 고품위급 모니터의 디지털 신호처리회로 구현)

  • 천성렬;김익환;이호근;하영호
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.28 no.11C
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    • pp.1152-1160
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    • 2003
  • Start The current paper proposes an improved HD(High Definition) monitor that can support a signal input with various resolutions. Due to the inadequate performance of the built-in digital PLL(Phase-locked Loop) of an ADC(Analog to Digital Converter) and poor tolerance of ADC ICs, there are problems in the stable processing of synchronization signals with various input signals. Accordingly, the proposed synchronization signal optimization technique regenerates the horizontal synchronization signal in the vertical blanking interval based on the regularity of the synchronization signal, i.e. the timing of the falling edge signal remains constant, thereby solving the above problem and minimizing the interference of the system. As a result, the proposed system can stabilize various synchronization signals with different resolution modes.

Bandpass Discrete Prolate Spheroidal Sequences and Its Applications to Signal Representation and Interpolation

  • Oh, Jin-Sung
    • Journal of the Institute of Convergence Signal Processing
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    • v.14 no.2
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    • pp.70-76
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    • 2013
  • In this paper, we propose the bandpass form of discrete prolate spheroidal sequences(DPSS) which have the maximal energy concentration in a given passband and as such are very appropriate to obtain a projection of signals. The basic properties of the bandpass DPSS are also presented. Assuming a signal satisfies the finite time support and the essential band-limitedness conditions with a known center frequency, signal representation and interpolation techniques for band-limited signals using the bandpass DPSS are introduced where the reconstructed signal has minimal out-of-band energy. Simulation results are given to present the usefulness of the bandpass DPSS for efficient representation of band-limited signal.

Design of Vector Register Architecture in DSP Processor for Efficient Multimedia Processing

  • Wu, Chou-Pin;Wu, Jen-Ming
    • JSTS:Journal of Semiconductor Technology and Science
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    • v.7 no.4
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    • pp.229-234
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    • 2007
  • In this paper, we present an efficient instruction set architecture using vector register file hardware to accelerate operation of general matrix-vector operations in DSP microprocessor. The technique enables in-situ row-access as well as column access to the register files. It can reduce the number of memory access significantly. The technique is especially useful for block-based video signal processing kernels such as FFT/IFFT, DCT/IDCT, and two-dimensional filtering. We have applied the new instruction set architecture to in-loop deblocking filter processing in H.264 decoder. Performance comparisons show that the required load/store operations for the in-loop deblocking filter can be reduced about 42%. The architecture would improve the processing speed, and code density in DSP microprocessor especially for video signal processing substantially.

Overview and Development of Digital SignalProcessing

  • Zhang, Chun-Xu;Shin, Yun-Ho
    • The Journal of the Korea institute of electronic communication sciences
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    • v.3 no.2
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    • pp.65-70
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    • 2008
  • Digital signal processing (DSP) is the process of taking a signal and performing an algorithm on it to analyze, modify, or better identify that signal.[1] To take advantage of DSP advances, one must have at least a basic understanding of DSP theory along with an understanding of the hardware architecture designed to support these new advances. There are several programming techniques that maximize the efficiency of the DSP hardware, as well as a few fundamental concepts used to implement DSP software. This article introduced some of these underlying functions that are the building blocks of complex signal processing functions, and It will touch on the fundamental concepts of DSP theory and algorithms and also provide an overview of the implementation and optimization of DSP software, and discuss the development of DSP.

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A Study on a Signal Processing Method for Detection of the Weld seam by Using Laser Displacement Sensor (레이저 변위센서를 이용한 용접선 검출에서 신호처리에 관한 연구)

  • ;;Kim, J. W.
    • Journal of Welding and Joining
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    • v.13 no.4
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    • pp.65-74
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    • 1995
  • The weld seam tracking sensor is indispensable to improve the flexibility of automatic arc welding systems. Among the position sensing methods available, a laser displacement sensor is one of the most prevailing methods. In this study, a laser displacement sensor was examined on detecting the weld seam of lap joints in sheet metal arc welding. The output signal of the laser displacement sensor may ontain severe fluctuation from the effect of arc light, spatters, fume, etc. So a variety of signal processing methods was applied to smooth the output signal of the sensor. And then the weld joint was determined by using the central difference method. It was revealed that the quadratic mean method plays an important role in detecting the weld seam during welding especially.

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Confirmation Method of Target Detection for Vehicle Mounted Metal Detector

  • Jung, Byung-Min;Shin, Beom-Su;Chang, YuShin;Yang, DongWon
    • Journal of the Korea Society of Computer and Information
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    • v.21 no.10
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    • pp.49-54
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    • 2016
  • In this paper, the confirmation method of target detection for the vehicle mounted metal detector (MD) has been described. The vehicle mounted MD with the arrayed 6 coils to detect the width of 2.4 m was demonstrated. It is important and necessary to inform the location of the objects detected by the MD. The confirmation method of target detection was verified by using the MD GUI and the analysis of the receive signal processing. The receive signal processing is performed by comparing the threshold and the difference of the signal calibrated at initial location and the signal detected at present location.