• Journal of Institute of Control, Robotics and Systems
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• v.21 no.1
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• pp.34-39
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• 2015

In this paper, a finite impulse response (FIR) filter is proposed for discrete-time nonlinear systems. The proposed filter is designed by combining the estimate of the perturbation state and nominal state. The perturbation state is estimated by adapting the optimal time-varying FIR filter for the linearized perturbation model and the nominal state is directly obtained from the nonlinear nominal trajectory model. Since the FIR structured estimators use the finite horizon information on the most recent time interval, the proposed extended FIR filter satisfies the bounded input/bounded output (BIBO) stability, which can't be obtained from infinite impulse response (IIR) estimators. Thus, it can be expected that the proposed extended FIR filter is more robust than IIR structured estimators such as an extended Kalman filter for the round-of errors and the uncertainties from unknown initial states and uncertain system model parameters. The simulation results show that the proposed filter has better performance than the extended Kalman filter (EKF) in both robustness and fast convergency.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.12
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• pp.1183-1187
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• 2011

In this paper, an optimal FIR (Finite-Impulse-Response) filter is proposed for discrete time-varying state-space models. The proposed filter estimates the current state using measured output samples on the recent time horizon so that the variance of the estimation error is minimized. It is designed to be linear, unbiased, with an FIR structure, and is independent of any state information. Due to its FIR structure, the proposed filter is believed to be robust for modeling uncertainty or numerical errors than other IIR filters, such as the Kalman filter. For a general system with system and measurement noise, the proposed filter is derived without any artificial assumptions such as the nonsingular assumption of the system matrix A and any infinite covariance of the initial state. A numerical example show that the proposed FIR filter has better performance than the Kalman filter based on the IIR (Infinite- Impulse-Response) structure when modeling uncertainties exist.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.413-418
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• 2003

In this paper, a new multirate optimal finite impulse response (FIR) filter is proposed for the signal reconstruction in the nosy filter bank systems. The multirate optimal FIR filter replaces the conventional synthesis filters and the Kalman synthesis filter. First, the generic linear model is derived from the multirate state space model for an autoregressive (AR)input signal. Second, the multirate optimal FIR filter is derived from the multirate generic linear model using the minimum variance criterion. This paper also provides numerical examples and results. The simulation results illustrate that the performance is improved compared with conventional synthesis filters and the proposed filter has advantages over the Kalman synthesis filter.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.980-983
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• 1996

A new version of the discrete-time optimal FIR (finite impulse response) filter utilizing only the measurements of finite sliding estimation window is suggested for linear time-invariant state-space models. This filter is called the BLUFIR (best linear unbiased finite impulse response) filter since it provides the BLUE (best linear unbiased estimate) of the state obtained from the measurements of the estimation window. It is shown that the BLUFIR filter has the deadbeat property when there are no noises in the estimation window.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.3
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• pp.437-447
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• 2003

We propose the methods to design the finite impulse response (FIR) and the infinite impulse response (IIR) lattice filters using Schur algorithm through the spectral factorization of the covariance matrix by circulant matrix factorization (CMF). Circulant matrix factorization is also very powerful tool used fur spectral factorization of the covariance polynomial in matrix domain to obtain the minimum phase polynomial without the polynomial root finding problem. Schur algorithm is the method for a fast Cholesky factorization of Toeplitz matrix, which easily determines the lattice filter parameters. Examples for the case of the FIR Inter and for the case of the IIR filter are included, and performance of our method check by comparing of our method and another methods (polynomial root finding and cepstral deconvolution).

• JSTS:Journal of Semiconductor Technology and Science
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• v.16 no.3
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• pp.261-273
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• 2016

Reconfigurable finite impulse response (FIR) filters whose filter coefficients and filter order change dynamically during run-time play an important role in the software defined radio (SDR) systems, multi-channel filters, and digital up/down converters. However, there are not many reports on such reconfigurable designs which can support dynamic variation of filter order and filter coefficients. The purpose of this paper is to provide an architectural solution for the FIR filters to support run-time variation of the filter order and filter coefficients. First, two straightforward designs, namely, (i) single-MAC based design and (ii) full-parallel design are presented. For large variation of the filter order, two designs based on (iii) folded structure and (iv) fast FIR algorithm are presented. Finally, we propose (v) high throughput design which provides significant advantage in terms of hardware and/or time complexities over the other designs. We compare complexities of all the five structures, and provide the synthesis results for verification.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.443-446
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• 2005

As modern society needs to process of acquisition, storage and transmission of much information, the importance of signal processing is increasing and various digital filters are used in the two-dimensional signal such as image. And kinds of these digital filters are IIR(infinite impulse response) filter and FIR(finite impulse response) filter. And FIR filter which has the phase linearity, the easiness of creation and stability is applied to many fields. In design of this FIR filter, flatness property is a important factor in pass-band and stop-band. In this paper, we designed a 2-D Circular FIR filter using the Bernstein polynomial, it is presented flatness property in pass-band and stop-band. And we simulated the designed filter with noisy test image and compared the results with existing methods.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.9
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• pp.807-810
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• 2015

In this paper, a finite impulse response(FIR) fixed-lag smoother is proposed for discrete-time nonlinear systems. If the actual state trajectory is sufficiently close to the nominal state trajectory, the nonlinear system model can be divided into two parts: The error-state model and the nominal model. The error state can be estimated by adapting the optimal time-varying FIR smoother to the error-state model, and the nominal state can be obtained directly from the nominal trajectory model. Moreover, in order to obtain more robust estimates, the linearization errors are considered as a linear function of the estimation errors. Since the proposed estimator has an FIR structure, the proposed smoother can be expected to have better estimation performance than the IIR-structured estimators in terms of robustness and fast convergence. Additionally the proposed method can give a more general solution than the optimal FIR filtering approach, since the optimal FIR smoother is reduced to the optimal FIR filter by setting the fixed-lag size as zero. To illustrate the performance of the proposed method, simulation results are presented by comparing the method with an optimal FIR filtering approach and linearized Kalman filter.

• The Journal of Korean Institute of Information Technology
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• v.16 no.11
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• pp.97-103
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• 2018

In this paper, the estimation method for the power signal harmonics is proposed by using the time-varying optimal finite impulse response (FIR) filter. To estimate the magnitude and phase-angle of the harmonic components, the time-varying optimal FIR filter is designed for the state space representation of the noisy power signal which the magnitude and phase is considered as a stochastic process. Since the time-varying optimal FIR filter used in the proposed method does not use any priori information of the initial condition and has FIR structure, the proposed method could overcome the demerits of Kalman filter based method such as poor estimation and divergence problem. Due to the FIR structure, the proposed method is more robust against to the model uncertainty than the Kalman filter. Moreover, the proposed method gives more general solution than the time-invariant optimal FIR filter based harmonic estimation method. To verify the performance and robustness of the proposed method, the proposed method is compared with time-varying Kalman filter based method through simulation.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.1
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• pp.49-55
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• 2003

The use of digital filters in the signal process field is increasing rapidly with development of the modern industrial society. Especially, detail processors, Y/C separators, ghost removing filters, standard converters (NTSC to PAL or PAL to NTSC) and noise reducers, all of which use digital filters, tend to be used in digital video and audio processing, CATV and various communication fields. Generally, there are two different digital filters, the Rf (infinite impulse response) filter and the FIR (finite impulse response) filter in digital filter. In this paper, we have designed FIR filter which has the phase linearity and the easiness of creation. In the design of the FIR digital filter, the window function is used to alleviate the ripples caused by Gibbs Phenomenon around the cut off frequency of the band pass. But there're some problems to choose proper window function for the design destination due to its fixed values. Therefore, in this paper, we designed a modified Hanning window with new parameter which is adaptively chosen corresponding to design objectives. The digital filter was simulated to prove the validity of the model and it was compared with the Hamming, the Manning, the Blacknan and the Kaiser window function. And we have used peak side-lobe and transient characteristics as standard of judgement.