• 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.

• Proceedings of the KIEE Conference
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• 1986.07a
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• pp.140-144
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• 1986

In this paper an FIR(finite impulse response) filter and smoother are introduced for discrete time-invariant state-space models with driving noises. The FIR structure not only quarantees the BIBO stability and the robustness to parameter changes but also improves the filter divergence problem. It is shown that the impulse responses of the FIR filter and the smoother are obtained by Riccati-type difference equations and that they are to be time-invariant and reduced to very simple forms. For implementational purpose, recursive forms of the FIR filler and smoother are derived with each other used as the adjoint variable.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2548-2551
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• 2005

In this paper, a robust receding horizon finite impulse response(FIR) filter is proposed for a class of linear discrete time systems with uncertainty satisfying an integral quadratic constraint. The robust state estimation problem involves constructing the set of all possible states at the current time consistent with given system input, output measurements and the integral quadratic constraint.

• 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).

• 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.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.1
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• pp.1-5
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• 2014

In this paper, we propose an optimal fixed-lag FIR (Finite-Impulse-Response) smoother for a class of discrete time-varying state-space signal models. The proposed fixed-lag FIR smoother is linear with respect to inputs and outputs on the recent finite horizon and estimates the delayed state so that the variance of the estimation error is minimized with the unbiased constraint. Since the proposed smoother is derived with system inputs, it can be adapted to feedback control system. Additionally, the proposed smoother can give more general solution than the optimal FIR filter, because it reduced to the optimal FIR filter by setting the fixed-lag size as zero. A numerical example is presented to illustrate the performance of the proposed smoother by comparing with an optimal FIR filter and a conventional fixed-lag Kalman smoother.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05b
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• pp.68-74
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• 2004

The use of digital filters in the signal processing field is increasing rapidly with development of the modem industrial society, and generally digital filter is classified into FIR (infinite impulse response) fillers and FIR (finite impulse response) filters. The FIR digital filter has the phase linearity and the easiness of creation. In the design of the FIR digital filter, the window function is used to alleviate ripples caused by Gibbs Phenomenon around the cut-off frequency of the passband. In this paper, we designed a new window function and compared with existing Manning, Hamming and Blackman window functions. And we used peak side-lobe and transient characteristics as standard of judgement.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.20 no.10
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• pp.35-40
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• 2006

In this paper, a current-mode analog variable finite-impulse-response (FIR) filter with variable tap coefficient circuits is proposed for frequency selective wireless personal area network(WPAN) system or terminals. From the circuit simulation the operation of the 7-tap FIR filter is confirmed. The 0.0625-step tap coefficient circuit is designed and fabricated with $0.8[{\mu}m]$ CMOS technology. The proposed FIR filter has a variable length of taps and variable coefficients, so it has a potential for being used to frequency selective WPAN system or frequency selective wireless communication terminals.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.11
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• pp.1057-1063
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• 2015

This paper proposes a new nonlinear filtering algorithm that combines the unscented Kalman filter (UKF) and the finite impulse response (FIR) filter. The proposed filter is called the unscented Kalman/FIR hybrid filter (UKFHF). In the UKFHF algorithm, the UKF is used as the main filter, which produces state estimates under ideal conditions. When failures of the UKF are detected, the FIR filter is operated. Using the output of the FIR filter, the UKF is reset and rebooted. In this way, the UKFHF recovers from failures. The proposed UKFHF is applied to indoor human localization using wireless sensor networks. Through simulations, the performance of the UKFHF is demonstrated in comparison with that of the UKF.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.912-916
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• 1992

In this paper we investigate the connection between the continuous-time FIR(finite impulse response) filter and the corresponding discrtet-time FIR filter with fast sampling. The interconnection is established by formulating the discrete-time case using delta operators which has superior numerical properties in discretizing prcedure. The aim of this paper is to present a unified FIR filter using the .delta.-operator and to show that, as sampling interval .DELYA. aperator to zero, the results of this filter converge to the corresponding continuous-time reuslts, which implies that the unified FIR filter unifies continous-time FIR filter and discrtet-time FIR filter.