• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제9권1호
• /
• pp.59-64
• /
• 2009

In this paper, we study the relations between L-fuzzy topologies and L-filters on a strictly two-sided, commutative quantale lattice L. We define an L-fuzzy neighborhood filter and introduce the notion of L-filter convergence in L-fuzzy topological spaces.

• Proceedings of the Korea Institute of Convergence Signal Processing
• /
• 한국신호처리시스템학회 2003년도 하계학술대회 논문집
• /
• pp.296-299
• /
• 2003

This paper shows a novel and simple IIR/FIR QMF(quadrature mirror filter) filter banks, mixed IIR and FIR structure. Here, FIR filters used for phase compensation. In this paper, we introduced analysis and synthesis filter banks, which used FIR linear phase filters and all pass filters. In result, phase response of analysis and synthesis filter banks become approximately linear characteristic. Simultaneously, a liasing distortion can be completely canceled.

• Journal of the Institute of Convergence Signal Processing
• /
• 제9권4호
• /
• pp.295-303
• /
• 2008

In general, transform domain adaptive filters show faster convergence speed than the time domain adaptive filters, but the amount of calculation increases dramatically as the filter order increases. This problem can be solved by making use of the subband structure in transform domain adaptive filters. In this paper, to increase the convergence speed on the generalized subband decomposition FIR adaptive filters, a structure of the adaptive filter with subfilter of dyadic sparsity factor in wavelet transform domain is designed. And, in this adaptive filter, the equivalent input in transform domain is derived and, by using the input, the convergence properties for the LMS algorithm is analyzed and evaluated. By using this sub band adaptive filter, the inverse system modeling and the periodic noise canceller were designed, and, by computer simulation, the convergence speeds of the systems on LMS algorithm were compared with that of the subband adaptive filter using DFT(discrete Fourier transform).

• Bulletin of the Korean Mathematical Society
• /
• 제45권2호
• /
• pp.207-220
• /
• 2008

We introduce and study the notions of supra fuzzy convergence of fuzzy filters, $s{\gamma}$-fuzzy open (closed) sets, $s{\gamma}(/TEX>$s{\gamma}^*)$-fuzzy continuous and $s{\gamma}$-fuzzy open mapping. Also. we investigate some of fundamental properties of these notions.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• 제30B권3호
• /
• pp.10-21
• /
• 1993

Bilinear models are attractive for adaptive filtering applications because they can approximate a large class of nonlinear systems adequately, and usually with considerable parsimony in the number of coefficients compared with Volterra models. But bilinear filters have stability problem because they involve nonlinear feedback. Adaptive algorithms for bilinear filters may be diverge and have poor convergence characteristics when input signal is large In this paper, necessary and sufficient condition for mean square stability of bilinear filters for given input signal statistics is briefly described, and the method obtaining the input bound to guarantee the stability of bilinear filters is presented. New RPEM algorithm, which does not diverge and has the superior convergence characteristics compared with the conventional RPEM algorithm when input signal is large, is derived by applying the time-varying Kalman filtering concept to the conventional RPEM algorithm.

• ETRI Journal
• /
• 제43권5호
• /
• pp.881-890
• /
• 2021

Photoplethysmography (PPG) is a noninvasive technique that can be used to conveniently measure heart rate (HR) and thus obtain relevant health-related information. However, developing an automated PPG system is difficult, because its waveforms are susceptible to motion artifacts and between-patient variation, making its interpretation difficult. We use deep neural network (DNN) filters to mimic the cognitive ability of a human expert who can distinguish the features of PPG altered by noise from various sources. Systolic (S), onset (O), and first derivative peaks (W) are recognized by three different DNN filters. In addition, the boundaries of uninformative regions caused by artifacts are identified by two different filters. The algorithm reliably derives the HR and presents recognition scores for the S, O, and W peaks and artifacts with only a 0.7-s delay. In the evaluation using data from 11 patients obtained from PhysioNet, the algorithm yields 8643 (86.12%) reliable HR measurements from a total of 10 036 heartbeats, including some with uninformative data resulting from arrhythmias and artifacts.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 한국퍼지및지능시스템학회 1997년도 추계학술대회 학술발표 논문집
• /
• pp.367-369
• /
• 1997

We introduce a notion of fuzzy L-convergence of filters and show that the collection of fuzzy L-convergence spaces forms a cartesian closed topological category.

• The Journal of the Acoustical Society of Korea
• /
• 제13권4호
• /
• pp.77-85
• /
• 1994

In this study an adaptive algorithm with optimum convergence factor for steepest descent method is proposed, which controls automatically the filter order to take the appropriate level. So far, fixed order filters have been used when adaptive filter is employed according to the priori knowledge or experience in various adaptive signal processing applications. But, it is so difficult to know the filter order needed in real implementations that high order filters have to be performed. As a result, redundant calculations are increased in the case of high order filters. The proposed variable length optimum convergence factor (VLOCF) algorithm takes the appropriated filter order within the given one so that the redundant calculation is decreased to get the enhancement of convergence speed and smaller convergence error during the steady state. The proposed algorithm is evaluated to prove the validity by computer simulation for system Identification.

• Journal of Radiopharmaceuticals and Molecular Probes
• /
• 제3권2호
• /
• pp.65-71
• /
• 2017

To assess the effects of filter and reconstruction of Cu-64 PET data on Siemens scanner, the various reconstruction algorithm with various filters were assessed in terms of spatial resolution, non-uniformity (NU), recovery coefficient (RC), and spillover ratio (SOR). Image reconstruction was performed using filtered backprojection (FBP), 2D ordered subset expectation maximization (OSEM), 3D reprojection algorithm (3DRP), and maximum a posteriori algorithms (MAP). For the FBP reconstruction, ramp, butterworth, hamming, hanning, or parzen filters were used. Attenuation or scatter correction were performed to assess the effect of attenuation and scatter correction. Regarding spatial resolution, highest achievable volumetric resolution was $3.08mm^3$ at the center of FOV when MAP (${\beta}=0.1$) reconstruction method was used. SOR was below 4% for FBP when ramp, Hamming, Hanning, or Shepp-logan filter were used. The lowest NU (highest uniform) after attenuation & scatter correction was 5.39% when FBP (parzen filter) was used. Regarding RC, 0.9 < RC < 1.1 was obtained when OSEM (iteration: 10) was used when attenuation and scatter correction were applied. In this study, image quality of Cu-64 on Siemens Inveon PET was investigated. This data will helpful for the quantification of Cu-64 PET data.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• 제21권4호
• /
• pp.876-883
• /
• 1996

Adaptive FIR filters are widely used in the echo canceller. But, most of practical systems have the transfer function composed of poles and zeros. In that case, adaptive IIR filters may be more efficient rather than FIR fiters. In this paper, a recently developed C-HARF algorithm is used to implement an adaptive IIR echo canceller. The proposed convergence of the algorithm make it attractive for this application. Extensive computer simulations show that C-HARF algorithm performs better than the NLMS algorithm after convergence, although C-HARF algorithm converges more slowly.