• Title/Summary/Keyword: Fast Convolution

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Fast Convolution Method using Psycho-acoustic Filters in Sound Reverberator (잔향 생성기에서 심리 음향 필터를 이용한 고속 컨벌루션 방법)

  • Shin, Min-Cheol;Wang, Se-Myung
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2007.11a
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    • pp.1037-1041
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    • 2007
  • With the advent of sound field simulator, many sound fields have been reproduced by obtaining the impulse responses of specific acoustic spaces like famous concert hall, opera house. This sound field reproduction has been done by the linear convolution operation between the sound input signal and the impulse response of certain acoustic space. However, the conventional finite impulse response based linear convolution operation always makes real-time implementation of sound field generator impossible due to the large amount of computational burden. This paper introduces the fast convolution method using perceptual redundancy in the processed signals, input audio signal and room impulse response. Temporal and spectral psycho-acoustic filters considering masking effects are implemented in the proposed convolution structure. It reduces the computational burden of convolution methods for realtime implementation of a sound field generator. The conventional convolutions are compared with the proposed one in views of computational burden and sound quality. In the proposed method, a considerable reduction in the computational burden was realized with acceptable changes in sound quality.

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Fast Convolution Method Using Real-time Masking Effects in Sound Reverberator (잔향 생성기에서 실시간 마스킹 효과를 이용한 고속 컨벌루션 방법)

  • Shin, Min-Cheol;Wang, Se-Myung
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.18 no.2
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    • pp.231-237
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    • 2008
  • With the advent of sound field simulator, many sound fields have been reproduced by obtaining the impulse responses of specific acoustic spaces like famous concert hall, opera house. This sound field reproduction has been done by the linear convolution operation between the sound input signal and the impulse response of certain acoustic space. However, the conventional finite impulse response based linear convolution operation always makes real-time implementation of sound field generator impossible due to the large amount of computational burden. This paper introduces the fast convolution method using perceptual redundancy in the processed signals, input audio signal and room impulse response. Temporal and spectral real-time masking blocks are implemented in the proposed convolution structure. It reduces the computational burden of convolution methods for real-time implementation of a sound field generator. The conventional convolutions are compared with the proposed one in views of computational burden and sound quality. In the proposed method, a considerable reduction in the computational burden was realized with acceptable changes in sound quality.

A Study on the Optimization of Convolution Operation Speed through FFT Algorithm (FFT 적용을 통한 Convolution 연산속도 향상에 관한 연구)

  • Lim, Su-Chang;Kim, Jong-Chan
    • Journal of Korea Multimedia Society
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    • v.24 no.11
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    • pp.1552-1559
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    • 2021
  • Convolution neural networks (CNNs) show notable performance in image processing and are used as representative core models. CNNs extract and learn features from large amounts of train dataset. In general, it has a structure in which a convolution layer and a fully connected layer are stacked. The core of CNN is the convolution layer. The size of the kernel used for feature extraction and the number that affect the depth of the feature map determine the amount of weight parameters of the CNN that can be learned. These parameters are the main causes of increasing the computational complexity and memory usage of the entire neural network. The most computationally expensive components in CNNs are fully connected and spatial convolution computations. In this paper, we propose a Fourier Convolution Neural Network that performs the operation of the convolution layer in the Fourier domain. We work on modifying and improving the amount of computation by applying the fast fourier transform method. Using the MNIST dataset, the performance was similar to that of the general CNN in terms of accuracy. In terms of operation speed, 7.2% faster operation speed was achieved. An average of 19% faster speed was achieved in experiments using 1024x1024 images and various sizes of kernels.

Application of the Convolution Method on the Fast Prediction of the Wind-Driven Current in a Samll Bay (소규모 만에서 취송류의 신속예측을 위한 convolution 기법의 적용)

  • 최석원;조규대;윤홍주
    • Journal of Environmental Science International
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    • v.8 no.3
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    • pp.299-307
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    • 1999
  • In order to fast predict the wind-driven current in a small bay, a convolution method in which the wind-driven current can be generated only with the local wind is developed and applied in the idealized bay and the idealized Sachon Bay. The accuracy of the convlution method is assessed through a series of the numerical experiements carried out in the jidealized bay and the idealized Sachon Bay. The optimum response function for the convolution method is obtained by minimizing the root man square (rms) difference between the current given by the numerical model and the current given by the convolution method. The north-south component of the response function shows simultaneous fluctuations in the wind and wind-driven current at marginal region while it shows "sea-saw" fluctuations (in which the wind and wind-driven current have opposite direction) at the central region in the idealized Sachon Bay. The present wind is strong enough to influence on the wind-driven current especially in the idealized Sachon Bay. The spatial average of the rms ratio defined as the ratio of the rms error to the rms speed is 0.05 in the idealized bay and 0.26 in the idealized Sachon Bay. The recover rate of kinetic energy(rrke) is 99% in the idealized bay and 94% in the idealized Sachon Bay. Thus, the predicted wind-driven current by the convolution model is in a good agreement with the computed one by the numerical model in the idealized bay and the idealized Sachon Bay.achon Bay.

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Study on the Fast Predication of the Wind-Driven Current in the Sachon Bay (사천만에서 취송류의 신속예측에 관한 연구)

  • 최석원;조규대;김동선
    • Journal of Environmental Science International
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    • v.8 no.3
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    • pp.309-318
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    • 1999
  • In order to fast predict the wind-driven current in a small bay, a convolution method in which the wind-driven current can be generated only wih the local wind is developed and applied in the Sachon Bay. The root mean square(rms) ratio defined as the ratio of the rms error to the rms speed is 0.37. The rms ratio is generally less than 0.2, except for all the mouths of Junju Bay and Namhae-do and in the region between Saryang Island and Sachon. The spatial average of the recover rate of kinetic energy(rrke) is 87%. Thus, the predicted wind-driven current by the convolution model is in a good agreement with the computed one by the numerical model. The raio of the difference between observed residual current (Vr) and predicted wind-driven current (Vc) to a residual current, that is, (Vr-Vc)/Vr shows 56%, 62% at 2 moorings in the Sachon Bay.

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Binary Image Based Fast DoG Filter Using Zero-Dimensional Convolution and State Machine LUTs

  • Lee, Seung-Jun;Lee, Kye-Shin;Kim, Byung-Gyu
    • Journal of Multimedia Information System
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    • v.5 no.2
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    • pp.131-138
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    • 2018
  • This work describes a binary image based fast Difference of Gaussian (DoG) filter using zero-dimensional (0-d) convolution and state machine look up tables (LUTs) for image and video stitching hardware platforms. The proposed approach for using binary images to obtain DoG filtering can significantly reduce the data size compared to conventional gray scale based DoG filters, yet binary images still preserve the key features of the image such as contours, edges, and corners. Furthermore, the binary image based DoG filtering can be realized with zero-dimensional convolution and state machine LUTs which eliminates the major portion of the adder and multiplier blocks that are generally used in conventional DoG filter hardware engines. This enables fast computation time along with the data size reduction which can lead to compact and low power image and video stitching hardware blocks. The proposed DoG filter using binary images has been implemented with a FPGA (Altera DE2-115), and the results have been verified.

A Study on the Probabilistic Generating Simulation by Fast Hartley Transform (Fast Hartley Transform을 이용한 확률론적 발전 시뮬레이션에 관한 연구)

  • 송길영;김용하;최재석
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.39 no.4
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    • pp.341-348
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    • 1990
  • This paper describes an algorithm for evaluating the Loss of Load Probability (LOLP) and calculating the production cost for all the generators in the system using Fast Hartley Transform (FHT). It also suggests the deconvolution procedure which is necessary for the generation expansion planning. The FHT is as fast as or faster than the Fast Fourier Transform (FFT) and serves for all the uses such as spectral, digital processing, and convolution to which the FFT is normally applied. The transformed function using FFT has complex numbers. However, the transformed function using FHT has real numbers and the convolution become quite simple. This method has been applied for the IEEE reliability test system and practical size model system. The test results show the effectiveness of the proposed method.

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Individual Pig Detection using Fast Region-based Convolution Neural Network (고속 영역기반 컨볼루션 신경망을 이용한 개별 돼지의 탐지)

  • Choi, Jangmin;Lee, Jonguk;Chung, Yongwha;Park, Daihee
    • Journal of Korea Multimedia Society
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    • v.20 no.2
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    • pp.216-224
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    • 2017
  • Abnormal situation caused by aggressive behavior of pigs adversely affects the growth of pigs, and comes with an economic loss in intensive pigsties. Therefore, IT-based video surveillance system is needed to monitor the abnormal situations in pigsty continuously in order to minimize the economic demage. Recently, some advances have been made in pig monitoring; however, detecting each pig is still challenging problem. In this paper, we propose a new color image-based monitoring system for the detection of the individual pig using a fast region-based convolution neural network with consideration of detecting touching pigs in a crowed pigsty. The experimental results with the color images obtained from a pig farm located in Sejong city illustrate the efficiency of the proposed method.

A Study on the Probabilistic Generation Simulation by FHT (Fast hartley Transform을 이용한 확률론적 발전시뮬레이션에 관한 연구)

  • Song, Kil-Yeoung;Kim, Yong-Ha;Choi, Jae-Seok
    • Proceedings of the KIEE Conference
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    • 1988.11a
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    • pp.131-134
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    • 1988
  • This Paper describes a algorithm for evaluating the loss of load probability of a generating system using Fast Hartley Transform. The Fast Hartley Transform(FHT) Is as fast as or faster than the Fast Fourier Transform(FHT) and serves for all the uses such as spectral, digital processing and convolution to which the FFT is at present applied. The method has been tested by applying to IEEE reliability test system and the effectiveness is demonstrated.

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A STUDY ON COMPARISION OF THE FFT AND FHT CYCLIC CONVOLUTION OF REAL SEQUENCE (REAL SEQUENCE의 CYCLIC CONVOLUTION을 이용한 FET와 FHT의 비교에 관한 연구)

  • Sung, Sang-Ki;Kim, Jin-Targ;Kim, Su-Il;Lee, Jin-Lee;Yang, Seung-In
    • Proceedings of the KIEE Conference
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    • 1987.07b
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    • pp.1188-1190
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    • 1987
  • Recently, new fast transform (such as discrete Hartley Transform) have been proposed which are best suited for the computation of real sequence. Two approaches using Fourier or Hartley transform are first compared. This paper is treated real sequence, compared number of addition of cyclic convolution with using the FFT and FHT the convolution technique is defined as a separating system impulse response to the given input and output of the system.

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