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Sergiy A Vorobyov - One of the best experts on this subject based on the ideXlab platform.

  • joint space slow time transmission with unimodular waveforms and receive Adaptive Filter Design for radar
    International Conference on Acoustics Speech and Signal Processing, 2018
    Co-Authors: Sergiy A Vorobyov
    Abstract:

    A novel computationally efficient method for jointly Designing the space-(slow) time (SST) transmission with unimodular waveforms and receive Adaptive Filter is developed for different radar configurations. The range sidelobe effect and Doppler characteristics are considered. In particular, we develop a novel approach for jointly synthesizing unimodular SST waveforms and minimum variance distortionless response receive Adaptive Filter for two cases of known Doppler information and presence of uncertainties on clutter bins. Corresponding non-convex optimization problems are formulated and efficient algorithms are derived. The main ideas of the algorithm developments are to decouple composite objective function of the formulated problems, generate minorizing surrogates, and then solve the joint Design problem iteratively, but in closed-form for each iteration by means of minorization - maximization technique. The proposed algorithms demonstrate good performance and have fast convergence speed and low complexity.

  • ICASSP - Joint Space-(Slow) Time Transmission with Unimodular Waveforms and Receive Adaptive Filter Design for Radar
    2018 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2018
    Co-Authors: Sergiy A Vorobyov
    Abstract:

    A novel computationally efficient method for jointly Designing the space-(slow) time (SST) transmission with unimodular waveforms and receive Adaptive Filter is developed for different radar configurations. The range sidelobe effect and Doppler characteristics are considered. In particular, we develop a novel approach for jointly synthesizing unimodular SST waveforms and minimum variance distortionless response receive Adaptive Filter for two cases of known Doppler information and presence of uncertainties on clutter bins. Corresponding non-convex optimization problems are formulated and efficient algorithms are derived. The main ideas of the algorithm developments are to decouple composite objective function of the formulated problems, generate minorizing surrogates, and then solve the joint Design problem iteratively, but in closed-form for each iteration by means of minorization - maximization technique. The proposed algorithms demonstrate good performance and have fast convergence speed and low complexity.

Mahdi Torabian Esfahani - One of the best experts on this subject based on the ideXlab platform.

  • Adaptive Filter Design based on the lms algorithm for delay elimination in tcr fc compensators
    Isa Transactions, 2011
    Co-Authors: Rahmat-allah Hooshmand, Mahdi Torabian Esfahani
    Abstract:

    Thyristor controlled reactor with fixed capacitor (TCR/FC) compensators have the capability of compensating reactive power and improving power quality phenomena. Delay in the response of such compensators degrades their performance. In this paper, a new method based on Adaptive Filters (AF) is proposed in order to eliminate delay and increase the response of the TCR compensator. The algorithm Designed for the Adaptive Filters is performed based on the least mean square (LMS) algorithm. In this Design, instead of fixed capacitors, band-pass LC Filters are used. To evaluate the Filter, a TCR/FC compensator was used for nonlinear and time varying loads of electric arc furnaces (EAFs). These loads caused occurrence of power quality phenomena in the supplying system, such as voltage fluctuation and flicker, odd and even harmonics and unbalancing in voltage and current. The above Design was implemented in a realistic system model of a steel complex. The simulation results show that applying the proposed control in the TCR/FC compensator efficiently eliminated delay in the response and improved the performance of the compensator in the power system.

Rahmat-allah Hooshmand - One of the best experts on this subject based on the ideXlab platform.

  • Adaptive Filter Design based on the lms algorithm for delay elimination in tcr fc compensators
    Isa Transactions, 2011
    Co-Authors: Rahmat-allah Hooshmand, Mahdi Torabian Esfahani
    Abstract:

    Thyristor controlled reactor with fixed capacitor (TCR/FC) compensators have the capability of compensating reactive power and improving power quality phenomena. Delay in the response of such compensators degrades their performance. In this paper, a new method based on Adaptive Filters (AF) is proposed in order to eliminate delay and increase the response of the TCR compensator. The algorithm Designed for the Adaptive Filters is performed based on the least mean square (LMS) algorithm. In this Design, instead of fixed capacitors, band-pass LC Filters are used. To evaluate the Filter, a TCR/FC compensator was used for nonlinear and time varying loads of electric arc furnaces (EAFs). These loads caused occurrence of power quality phenomena in the supplying system, such as voltage fluctuation and flicker, odd and even harmonics and unbalancing in voltage and current. The above Design was implemented in a realistic system model of a steel complex. The simulation results show that applying the proposed control in the TCR/FC compensator efficiently eliminated delay in the response and improved the performance of the compensator in the power system.

  • Adaptive Filter Design based on the LMS algorithm for delay elimination in TCR/FC compensators.
    ISA Transactions, 2011
    Co-Authors: Rahmat-allah Hooshmand, Torabian Esfahani
    Abstract:

    Thyristor controlled reactor with fixed capacitor (TCR/FC) compensators have the capability of compensating reactive power and improving power quality phenomena. Delay in the response of such compensators degrades their performance. In this paper, a new method based on Adaptive Filters (AF) is proposed in order to eliminate delay and increase the response of the TCR compensator. The algorithm Designed for the Adaptive Filters is performed based on the least mean square (LMS) algorithm. In this Design, instead of fixed capacitors, band-pass LC Filters are used. To evaluate the Filter, a TCR/FC compensator was used for nonlinear and time varying loads of electric arc furnaces (EAFs). These loads caused occurrence of power quality phenomena in the supplying system, such as voltage fluctuation and flicker, odd and even harmonics and unbalancing in voltage and current. The above Design was implemented in a realistic system model of a steel complex. The simulation results show that applying the proposed control in the TCR/FC compensator efficiently eliminated delay in the response and improved the performance of the compensator in the power system.

Nurettin Acir - One of the best experts on this subject based on the ideXlab platform.

  • A novel Adaptive Filter Design using Lyapunov stability theory
    TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES, 2015
    Co-Authors: Engin Cemal Menguc, Nurettin Acir
    Abstract:

    This paper presents a new approach to Design an Adaptive lter using Lyapunov stability theory. The Design procedure is formulated as an inequality constrained optimization problem. Lagrange multiplier theory is used as an optimization tool. Lyapunov stability theory is integrated into the constraint function to satisfy the asymptotic stability of the proposed ltering system. The tracking capability is improved by using a new analytical adaptation gain rate, which has the ability to Adaptively adjust itself depending on a sequential tracking square error rate. The fast and robust convergence ability of the proposed algorithm is comparatively examined by simulation examples.

  • lyapunov stability theory based complex valued Adaptive Filter Design
    Signal Processing and Communications Applications Conference, 2014
    Co-Authors: Engin Cemal Menguc, Nurettin Acir
    Abstract:

    In this study, a novel complex valued Adaptive Filter algorithm is proposed satisfying stability in the sense of Lyapunov. The prediction capability of the proposed algorithm is presented by using complex valued autoregressive process and wind signal in the literature. The proposed complex valued Adaptive Filter algorithm is compared with standard complex normalized least mean square algorithm and performed in a high performance.

  • SIU - Lyapunov stability theory based complex valued Adaptive Filter Design
    2014 22nd Signal Processing and Communications Applications Conference (SIU), 2014
    Co-Authors: Engin Cemal Menguc, Nurettin Acir
    Abstract:

    In this study, a novel complex valued Adaptive Filter algorithm is proposed satisfying stability in the sense of Lyapunov. The prediction capability of the proposed algorithm is presented by using complex valued autoregressive process and wind signal in the literature. The proposed complex valued Adaptive Filter algorithm is compared with standard complex normalized least mean square algorithm and performed in a high performance.

  • SIU - A novel nonlinear Adaptive Filter Design and its implementation with FPGA
    2012 20th Signal Processing and Communications Applications Conference (SIU), 2012
    Co-Authors: Engin Cemal Menguc, Nurettin Acir
    Abstract:

    In this study, a novel nonlinear Adaptive Filter algorithm is proposed guaranteeing the asymptotic stability in the sense of Lyapunov. The tracking capability of the proposed Filter is tested by using a created artificial signal having a finite number of discontinuities. The proposed Filter shows high performance both in Matlab environment and its FPGA realization. As a result, realization of the proposed Filter with FPGA is confirmed.

Chih-min Lin - One of the best experts on this subject based on the ideXlab platform.

  • Adaptive Filter Design for active noise cancellation using recurrent type-2 fuzzy brain emotional learning neural network
    Neural Computing and Applications, 2019
    Co-Authors: Tien-loc Le, Tuan-tu Huynh, Chih-min Lin
    Abstract:

    This article aims to develop a more efficient Adaptive Filter for the active noise cancellation (ANC). A novel recurrent interval type-2 fuzzy brain emotional learning Filter (RT2BELF) is proposed for achieving favourable Filtering performance. The ANC is a method to eliminate noise by creating an anti-noise signal which has the same magnitude but opposite phase with the unwanted noise. In order to adapt to the change of the noise, the parameters for the RIT2BELF are online updated based on the Adaptive laws, which are derived by the steepest descent gradient approach. The performance of the proposed ANC Design method is successfully demonstrated based on numerical simulation results in the real signals. Finally, the superiority of the proposed method is confirmed by the results comparison with some noise cancellation methods.

  • Adaptive Filter Design Using Type-2 Fuzzy Cerebellar Model Articulation Controller
    IEEE Transactions on Neural Networks and Learning Systems, 2016
    Co-Authors: Chih-min Lin, Ming-shu Yang, Fei Chao, Jun Zhang
    Abstract:

    This paper aims to propose an efficient network and applies it as an Adaptive Filter for the signal processing problems. An Adaptive Filter is proposed using a novel interval type-2 fuzzy cerebellar model articulation controller (T2FCMAC). The T2FCMAC realizes an interval type-2 fuzzy logic system based on the structure of the CMAC. Due to the better ability of handling uncertainties, type-2 fuzzy sets can solve some complicated problems with outstanding effectiveness than type-1 fuzzy sets. In addition, the Lyapunov function is utilized to derive the conditions of the Adaptive learning rates, so that the convergence of the Filtering error can be guaranteed. In order to demonstrate the performance of the proposed Adaptive T2FCMAC Filter, it is tested in signal processing applications, including a nonlinear channel equalization system, a time-varying channel equalization system, and an Adaptive noise cancellation system. The advantages of the proposed Filter over the other Adaptive Filters are verified through simulations.

  • Adaptive Filter Design Using Recurrent Cerebellar Model Articulation Controller
    IEEE Transactions on Neural Networks, 2010
    Co-Authors: Chih-min Lin, Li-yang Chen, Daniel S. Yeung
    Abstract:

    A novel Adaptive Filter is proposed using a recurrent cerebellar-model-articulation-controller (CMAC). The proposed locally recurrent globally feedforward recurrent CMAC (RCMAC) has favorable properties of small size, good generalization, rapid learning, and dynamic response, thus it is more suitable for high-speed signal processing. To provide fast training, an efficient parameter learning algorithm based on the normalized gradient descent method is presented, in which the learning rates are on-line adapted. Then the Lyapunov function is utilized to derive the conditions of the Adaptive learning rates, so the stability of the Filtering error can be guaranteed. To demonstrate the performance of the proposed Adaptive RCMAC Filter, it is applied to a nonlinear channel equalization system and an Adaptive noise cancelation system. The advantages of the proposed Filter over other Adaptive Filters are verified through simulations.