• 한국소음진동공학회논문집
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• 제18권2호
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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.

• 대한음성학회지:말소리
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• 제51호
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• pp.85-98
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• 2004

It is almost impossible to generate the sound field effect in real time with the time-domain linear convolution because of its large multiplication operation requirement. To solve this, three methods are introduced to reduce the number of multiplication operations in this paper. Firstly, the time-domain linear convolution is replaced with the frequency-domain circular convolution. In other words, the linear convolution result can be derived from that of the circular convolution. This technique reduces the number of multiplication operations remarkably, Secondly, a subframe concept is introduced, i.e., one original frame is divided into several subframes. Then the FFT is executed for each subframe and, as a result, the number of multiplication operations can be reduced. Finally, the QFT is used in stead of the FFT. By combining all the above three methods into our final the SFE generation algorithm, the number of computations are reduced sufficiently and the real-time SFE generation becomes possible with a general PC.

• 대한음성학회지:말소리
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• 제47호
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• pp.85-96
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• 2003

It is difficult to implement sound field effect on real time using linear convolution in time domain because linear convolution needs much multiply operations. In this paper three ways is introduced to reduce multiplication operations. Firstly, linear convolution in time domain is replaced with circular convolution in frequency domain. It means that it operates multiplication in place of convolution. Secondly, one frame will be divided into several frames. It will reduce the multiplication operation in processing that transforms time domain into frequency domain. Finally, QFT will be used in place of FFT. Three ways result much reduction in multiplication operations. The reduction of the multiplication operation makes the real time implementation possible.

• 한국멀티미디어학회논문지
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• 제19권1호
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• pp.80-85
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• 2016

It costs high in both memory usage and time consuming to sample the space to compute charge density and calculate electric field on that with large size of plasma data. In real-time and interactive application, accelerating the compute time is critical problem. In this paper, we suggest new method to visualize electric field by using convolution theorem, and the parallel computing to accelerate computing time by using GPGPU. We conduct a simulation that compare running time between the methods with convolution and without convolution. We discussed the method of visualization of multivariate data in three dimensional space using colored volume rendering and surface construction.

• 전기전자학회논문지
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• 제20권3호
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• pp.303-306
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• 2016

본 논문에서는 GPGPU를 활용하여 Convolutional neural network의 가속화 방법을 제안한다. Convolutional neural network는 이미지의 특징 값을 학습하여 분류하는 neural network의 일종으로 대량의 데이터를 학습해야하는 영상 처리에 적합하다. 기존의 Convolutional neural network의 convolution layer는 다수의 곱셈 연산을 필요로 하여 임베디드 환경에서 실시간으로 동작하기에 어려움이 있다. 본 논문에서는 이러한 단점을 해결하기 위하여 winograd convolution 연산을 통하여 곱셈 연산을 줄이고 GPGPU의 SIMT 구조를 활용하여 convolution 연산을 병렬 처리한다. 실험은 ModelSim, TestDrive를 사용하여 진행하였고 실험 결과 기존의 convolution 연산보다 처리 시간이 약 17% 개선되었다.

• 한국인공지능학회지
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• 제11권3호
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• pp.17-22
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• 2023

In this paper, we propose a black ice detection system using Convolutional Neural Networks (CNNs). Black ice poses a serious threat to road safety, particularly during winter conditions. To overcome this problem, we introduce a CNN-based architecture for real-time black ice detection with an encoder-decoder network, specifically designed for real-time black ice detection using thermal images. To train the network, we establish a specialized experimental platform to capture thermal images of various black ice formations on diverse road surfaces, including cement and asphalt. This enables us to curate a comprehensive dataset of thermal road black ice images for a training and evaluation purpose. Additionally, in order to enhance the accuracy of black ice detection, we propose a multi-scale dilation convolution feature fusion (MsDC-FF) technique. This proposed technique dynamically adjusts the dilation ratios based on the input image's resolution, improving the network's ability to capture fine-grained details. Experimental results demonstrate the superior performance of our proposed network model compared to conventional image segmentation models. Our model achieved an mIoU of 95.93%, while LinkNet achieved an mIoU of 95.39%. Therefore, it is concluded that the proposed model in this paper could offer a promising solution for real-time black ice detection, thereby enhancing road safety during winter conditions.

• Smart Structures and Systems
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• 제17권5호
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• pp.753-771
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• 2016

This paper addresses the free and transient responses of a SDOF linear complex stiffness system by making use of the Hilbert transform and the convolution integral. Because the second-order differential equation of motion having the complex stiffness give rise to the conjugate complex eigen values, its time-domain analysis using the standard time integration scheme suffers from the numerical instability and divergence. In order to overcome this problem, the transient response of the linear complex stiffness system is obtained by the convolution integral of a green function which corresponds to the unit-impulse free vibration response of the complex system. The damped free vibration of the complex system is theoretically derived by making use of the state-space formulation and the Hilbert transform. The convolution integral is implemented by piecewise-linearly interpolating the external force and by superimposing the transient responses of discretized piecewise impulse forces. The numerical experiments are carried out to verify the proposed time-domain analysis method, and the correlation between the real and imaginary parts in the free and transient responses is also investigated.

• Journal of applied mathematics & informatics
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• 제41권3호
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• pp.553-567
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• 2023

There are real life situations in our lives where the things are changing continuously or from time to time. It is a very important problem for one whether to continue the existing relationship or to form a new one after some occasions. That is, people, companies, cities, countries, etc. may change their opinion or position rapidly. In this work, we think of the problem of changing relationships from a mathematical point of view and think of an answer. In some sense, we comment these changes as power changes. Our number theoretical model will be based on this idea. Using the convolution sum of the restricted divisor function E, we obtain the answer to this problem.

• 대한기계학회논문집A
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• 제38권3호
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• pp.283-288
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• 2014

로봇에 대한 필요성이 더 이상 산업용 로봇에 국한되지 않고 서비스 로봇 혹은 의료 로봇으로 확대됨에 따라 사람과의 공존을 위해 외부 환경에 즉각적으로 대응이 가능한 궤적 생성 방법이 요구되고 있다. 이에 본 논문에서는 컨볼루션 연산을 이용한 실시간으로 변경 가능한 궤적 생성 방법을 제시한다. 본 논문에서 제시하는 방법은 기존의 컨볼루션 방법과 같이, 시스템의 운동학적 제약 조건 내에서의 궤적을 생성하며 기존 컨볼루션 방법의 모든 특성을 만족한다. 또한, 항상 사다리꼴 모양으로 궤적이 생성되는 특성으로 인한 특정 상황에서 비효율적으로 궤적이 생성될 수 있는 기존 컨볼루션 방법의 단점을 개선시키는 새로운 방법을 제시한다. 모의 실험을 통해 제안하는 방법의 유효성과 적합성을 보이며, 기존 컨볼루션 방법과의 비교를 통해 그 효율성을 보인다.

• 반도체디스플레이기술학회지
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• 제20권3호
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• pp.125-130
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• 2021

Scaffold is used to produce bio sensor. Scaffold is required high dimensional accuracy. 3D printer is used to manufacture scaffold. 3D printer can't detect defect during printing. Defect detection is very important in scaffold printing. Real-time defect detection is very necessary on industry. In this paper, we proposed the method for real-time scaffold defect detection. Real-time defect detection model is produced using CNN(Convolution Neural Network) algorithm. Performance of the proposed model has been verified through evaluation. Real-time defect detection system are manufactured on hardware. Experiments were conducted to detect scaffold defects in real-time. As result of verification, the defect detection system detected scaffold defect well in real-time.