• The KIPS Transactions:PartB
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• v.8B no.4
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• pp.395-402
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• 2001

본 논문에서는, 1차원 및 2차원 웨이브렛 함수를 전역통과필터(APF)와 지연기의 병렬접속에 위한 재귀형(IIR) 디지털 필터로 구성하는 방법을 제안한다. Mallat에 의하여 웨이브렛 변환과 필터뱅크가 밀접한 관계에 있다는 것이 알려졌고, 완전 재구성 필터뱅크로부터 웨이브렛 함수를 도출하는 다양한 방법이 알려져 있다. 그러나, 이러한 방법의 대부분은 비재귀형(FIR) 디지털 필터에 근거를 두는 것으로, 재귀형 디지털 필터에 의한 방법은 거의 제안되어 있지 않다. 재귀형 필터를 이용하는 장점은 비재귀형에 비하여 낮은 차수로 표현되는 점이다. 또 직교 웨이브렛 함수를 끌어내기 위한 직교조건을 용이하게 만족시킬 수 있다. 본 논문에서는 웨이브렛 함수에 요구되는 레귤레리티(Regularity)조건을 만족시키기 위하여, 최대 평탄성(Maximally Flat)을 부가한 새로운 1차원 및 2차원 재귀형 웨이브렛 함수의 도출법을 보인다.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.1
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• pp.73-77
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• 2007

In this paper, we propose a VLSI architecture of an LMS filter based on a Cyclo-static scheduler for fast computation of LMS filteing algorithm which is widely used in adptive filtering area. This process is composed of two steps: scheduling and circuit synthesis. The scheduling step accepts a fully specified flow graph(FSFG) as an input, and generates an optimal Cyclo-static schedule in the sense of the sampling rate, the number of processors, and the input-output delay. Then the generated schedule is transformed so that the number of communication edges between the processors. The circuit synthesis part translates the modified schedule into a complete circuit diagram by performing resource allocations. The VLSI layout generation can be performed easily by an existing silicon compiler.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.12
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• pp.1926-1933
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• 2022

Parameterized multichannel Wiener filter (PMWF) is a linear filter that can control the trade-off between residual noise and signal distortion using the embedded parameter. To apply the PMWF to noisy inputs, accurate noise estimation is important and multichannel minima-controlled recursive averaging (MMCRA) is widely used. However, in the case of the MMCRA, the accuracy of noise estimation decreases when a directional interference is involved into the array inputs. Consequently, the performance of the PMWF is degraded. Therefore, we propose a noise power spectral density (PSD) estimation method for the PMWF in this paper. The proposed method is based on a consecutive process of eigenvalue decomposition on noisy input PSD, estimation of the target component contribution using directional information, and exponential weighting for improved estimation of the target contribution. For evaluation, four objective measures were compared with the MMCRA and we verify that the PMWF with the proposed noise estimation method can improve performance in environments where directional interfereces exist.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.2
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• pp.159-164
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• 2004

This paper proposes a new digital filter implementation which adopts an identical structure at both behavioral and logic level in top-down design. This methodology is based on the observation that multiplication is a form of convolution and carrying, and therefore multiplication is implemented with the same structure as that of a convolution in a recursive manner at the logic level. In order to demonstrate a recursive structure-based FIR digital filter, we select L-tap transposed and systolic FIR filters, and implement them to have a single structure. The proposed filter design becomes regular and modular because of the recursive adoption of a single structure for convolutions, and is very compact in that it needs only two 1-bit I/O ports in addition to significant improvement on hardware complexity without time penalty on the output sequence.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.6
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• pp.136-142
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• 1994

This study presents an algorithm and related techniques which could satisfy the important properties of check weighers and conveyor scales. The algorithm of Recursive Least Squares Regression is described for te weighing system simulated as a dynamic model of the second order. Using the model and the algorithm, model parameters and then the mass being weighed can be determined from the step input. The performance of the algorithm is illustrated in digital simulation. Discussions are extended to the development of fast converging algorithm. It turns out that the algorithm shows several desirable features suitable for microcomputer assisted real-time signal processing, which are high precision and stability in noisy environment.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.44 no.4
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• pp.298-307
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• 2016

Attitude determination of satellite is categorized by deterministic and recursive method. The recursive algorithm using Kalman filter is widely used. Cubesat has limitation for payload to minimize then only two attitude sensors are installed which are sun sensor and magnetometer. Sun sensor measurements are useless during eclipse, however cubesat keeps estimating attitude to complete the successful mission. In this paper, Attitude determination algorithm based on Kalman filter is developed by additional term which considering the dynamics for SNUSAT-1 with disturbance torque. Verification of attitude accuracy of the algorithm is conducted during eclipse. Attitude determination algorithm is simulated to compare the performance between typical method and proposed algorithm. In addition, Attitude errors are analysed with various magnitude of disturbance torque caused by space environment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.758-761
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• 2007

Digital signal processing technique is applied in wide fields such as speech processing, image processing and spectrum analysis. Therefore, in order to do frequency selective operation digital filter is used in stead of analog filter and sharp filter characteristics can be implemented. Since finite impulse response (FIR) digital filter as nonrecursive type represents linear phase response characteristics and is always stable and is used in fields regarding wave information importantly such as data transmission. And due to frequency characteristics, in order to remove the Gibbs phenomenon generating around a discontinuous point, filter is designed through window function method. Therefore, in this paper to improve performance of FIR digital filter, a modified window function was applied. And the proposed method was compared with conventional methods using peak side-lobe and transition properties in simulations.

• The Journal of the Acoustical Society of Korea
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• v.40 no.5
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• pp.452-459
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• 2021

Estimating the mutual time delay between two acoustic sensors is used in various fields such as tracking and estimating the location of a target in room acoustics and sonar. In the time delay estimation methods, there are a non-parametric method, such as Generalized Cross Correlation (GCC), and a parametric method based on system identification. In this paper, we propose a time delay estimation method based on the parametric method. In particular, we propose a method that considers the noise in each receiving acoustic sensor. Simulation confirms that the proposed algorithm is superior to the existing generalized cross-correlation and adaptive eigenvalue analysis methods in white noise and reverberation environments.

• The Journal of the Acoustical Society of Korea
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• v.40 no.3
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• pp.213-218
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• 2021

It is known that total least-squares method shows better estimation performance than least-squares method when noise is present at the input and output at the same time. When total least squares method is applied to data with time series characteristics, Recursive Total Least Squares (RTS) algorithm has been proposed to improve the real-time performance. However, RTLS has numerical instability in calculating the inverse matrix. In this paper, we propose an algorithm for reducing numerical instability as well as having similar convergence to RTLS. For this algorithm, we propose a new RTLS using Iterative Wiener Filter (IWF). Through the simulation, it is shown that the convergence of the proposed algorithm is similar to that of the RTLS, and the numerical robustness is superior to the RTLS.