• 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.

• 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).

• 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 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.

• 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.

• International journal of advanced smart convergence
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• v.4 no.2
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• pp.138-144
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• 2015

Digital filters are extensively used in the world of communication. In order to design a digital finite impulse response (FIR) filter that satisfies all the required conditions is challenging. In this paper, design techniques of digital low pass FIR filters using Rectangular window method, Hamming window, Hanning window, and Optimal Parks McClellan method are presented. The stability, number of components required and filter coefficients are demonstrated for different design techniques. It is demonstrated that filter design using hamming window is comparatively better than rectangular and hanning window though the components required for all of the windowing technique are same, hamming shows higher stability. The stability is shown with the help of magnitude and phase spectrum of each window. Simulation is carried out using MATLAB and comparisons are made entirely based on the output of the simulation.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.31-38
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• 2024

The digital phase-locked loop(DPLL) is one of the circuits composed of a digital detector, digital loop filter, voltage-controlled oscillator, and divider as a fundamental circuit, widely used in many fields such as electrical and circuit fields. A state estimator using various mathematical algorithms is used to improve the performance of a digital phase-locked loop. Traditional state estimators have utilized Kalman filters of infinite impulse response state estimators, and digital phase-locked loops based on infinite impulse response state estimators can cause rapid performance degradation in unexpected situations such as inaccuracies in initial values, model errors, and various disturbances. In this paper, we propose a two-layer Frobenius norm-based finite impulse state estimator to design a new digital phase-locked loop. The proposed state estimator uses the estimated state of the first layer to estimate the state of the first layer with the accumulated measurement value. To verify the robust performance of the new finite impulse response state estimator-based digital phase locked-loop, simulations were performed by comparing it with the infinite impulse response state estimator in situations where noise covariance information was inaccurate.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.41 no.1
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• pp.35-44
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• 2004

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 for 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 filter and for the case of the In filter are included, and performance of our method check by comparing of our method and another methods (polynomial root finding and cepstral deconvolution).

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.445-448
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• 1996

For a lightly damped system, IIR based filter can have better performance than FIR filter as an adaptive filter in ANC algorithm. IIR based filter which has an infinite impulse response can model a lightly damped acoustic system with a small number of weights compared that of FIR filter and has no nonlinearity and instability problems on weight updating process which are associated to the conventional IIR filters. There are, however, some drawbacks such as design parameters to be determined earlier to get better performance and much increased computational power especially in the presence of error path. In this study, base filter parameters are determined in systematic manner, with the knowledge of the nominal impulse response of the system which should be identified, by Prony's method. Three methods reducing the computational load are proposed and their performance and application limits are discussed. Simulation and experimental results demonstrate the feasibility of the proposed method.