Adaptive Transversal Filter Research Articles

A modified simplex based direct search optimization algorithm for adaptive transversal FIR filters.

In this paper, a novel modified optimization algorithm is presented, which combines Nelder-Mead (NM) method with a gradient-based approach. The well-known Nelder Mead optimization technique is widely used but it suffers from convergence issues in higher dimensional complex problems. Unlike the NM, in this proposed technique we have focused on two issues of the NM approach, one is shape of the simplex which is reshaped at each iteration according to the objective function, so we used a fixed shape of the simplex and we regenerate the simplex at each iteration and the second issue is related to reflection and expansion steps of the NM technique in each iteration, NM used fixed value of , that is, = 1 for reflection and = 2 for expansion and replace the worst point of the simplex with that new point in each iteration. In this way NM search the optimum point. In proposed algorithm the optimum value of the parameter is computed and then centroid of new simplex is originated at this optimum point and regenerate the simplex with this centroid in each iteration that optimum value of will ensure the fast convergence of the proposed technique. The proposed algorithm has been applied to the real time implementation of the transversal adaptive filter. The application used to demonstrate the performance of the proposed technique is a well-known convex optimization problem having quadratic cost function, and results show that the proposed technique shows fast convergence than the Nelder-Mead method for lower dimension problems and the proposed technique has also good convergence for higher dimensions, that is, for higher filter taps problem. The proposed technique has also been compared with stochastic techniques like LMS and NLMS (benchmark) techniques. The proposed technique shows good results against LMS. The comparison shows that the modified algorithm guarantees quite acceptable convergence with improved accuracy for higher dimensional identification problems.

INCREASE OF EFFICIENCY OF SUPPRESSION OF THE ACTIVE NOISE JAMMING IN RADAR INTERCEPTION OF AIR TARGETS IN THE REVIEW MODE

The modified algorithm of the adaptive compensating of the active noise jamming, based on usage of the recurrence estimation of inverse covariance matrix of jamming in the course of an self-tuning is considered. The matrix estimation is formed by a method of a serial regression (SRM), a consequence application of a lemma about inversing of a matrix to differential – to the difference equation for a rounded estimation of direct covariance matrix of jamming (CMJ). The single estimation of straight line CMJ is formed as result dyad products of the instant vectors of noises in handling channels. In partial channels the adaptive transversal filters with the self-tuning on value of a signal of an aggregate error are implemented.In article skeleton diagrams of devices of the compensating implemented by various methods are resulted. Mathematical modeling of operation of the algorithms, implemented by a method of the least squares (criterion of a minimum RMS error) and a method of a serial regression is performed.Results of mathematical modeling of operation of the device of compensating of active noises jamming in the conditions of the active radio-electronic counteraction at multipath propagation of signals both non-identical amplitude and phase characteristics of channels of handling are resulted. Optimal values of technical parameters of devices of compensating of the active noises jamming providing obtaining of demanded values of coefficient of suppression are given. The comparative analysis of indexes of efficiency of classical and offered algorithms of compensating is made. Advantage of algorithm of compensating of the active noises jamming, using the recurrence estimation of a inverse covariance matrix of jamming is shown.The algorithm of functioning on the basis of SRM allows to lower essentially requirements to specialized VLSI (FPGA) at implementation is hardware – program complexes for preprocessing of the radar, radio communication and radio – navigation information in the conditions of influence of the active noises jamming in the presence of effects of multipath propagation of signals, in the presence of delay of signals on an antenna system aperture, and also at unremovable technological dispersion amplitude and phase characteristics of the microwave of channels of handling.

A reduced bias delay lock loop for adaptive filters

Narrowband interferences (NBIs) severely degrade the quality of a received signal and can hinder the operation of GPS receivers, and therefore, they are commonly excised using an adaptive transversal filter. This filter does not cause code tracking bias in the case of an ideal analog receiver channel when its magnitude and phase response are constant; however, distortion is induced by RF cables, amplifiers, and mixers that results in an asymmetric correlation function. This correlation function is further deformed by the adaptive transversal filter, resulting in a nonzero bias. Given the adaptive nature of this transversal filter, the bias varies based on the jamming pattern. For precision navigation applications, this bias must be mitigated. With this problem in mind, a new technique called amplitude estimating delay lock loop (AEDLL) is presented. By using data related to a known structure of the adaptive transversal filter, the proposed method only needs to estimate the amplitude of the correlation function and revise the correlation function for code tracking. Simulations show that the AEDLL method is capable of reducing the RMSE of code tracking bias to less than 0.12ns, which is significantly smaller than that achieved using existing methods.

Modeling of memristor-based chaotic systems using nonlinear Wiener adaptive filters based on backslash operator

Memristor-based chaotic systems have complex dynamical behaviors, which are characterized as nonlinear and hysteresis characteristics. Modeling and identification of their nonlinear model is an important premise for analyzing the dynamical behavior of the memristor-based chaotic systems. This paper presents a novel nonlinear Wiener adaptive filtering identification approach to the memristor-based chaotic systems. The linear part of Wiener model consists of the linear transversal adaptive filters, the nonlinear part consists of nonlinear adaptive filters based on the backslash operator for the hysteresis characteristics of the memristor. The weight update algorithms for the linear and nonlinear adaptive filters are derived. Final computer simulation results show the effectiveness as well as fast convergence characteristics. Comparing with the adaptive nonlinear polynomial filters, the proposed nonlinear adaptive filters have less identification error.

A Noise‐Free Adaptive Transversal Notch Filter Using the SSCF Algorithm with Decorrelation Parameter

SUMMARYAdaptive notch filters composed of an adaptive transversal filter have the limitation of bias error resulting from the broadband signal included in the input signal. In this paper, we propose an adaptive notch filter with a smaller bias error using a new adaptive algorithm based on the square sum of the correlation function with decorrelation parameter (SSCF‐DP). The cost function of the SSCF‐DP algorithm is the square sum of the cross‐correlation coefficient of the input and output error signal with the decorrelation parameter. The analytical results and the features described above are verified by computer simulation.

Modeling of Hysteresis in Piezoelectric Actuator Using Linear Play Operator Adaptive Filter

Piezoelectric actuator (PEA) is widely applied in micro/nanopositioning system. However, its inherent hysteresis limits its application. Modeling of hysteresis plays an important role in solving this problem. Linear play operators (LPO) adaptive hysteresis model is introduced in this paper. LPO operators are used to replace delay operators of adaptive transversal filter to compose a new serial structure of adaptive transversal filter model, and LMS (Least Mean Square) algorithm is used to adjust the weight values. As hysteresis loop of piezoelectric actuator is asymmetric and LPO operator is symmetric, a modified LPO (MLPO) adaptive filter is proposed for asymmetric hysteresis effect. At last, the two LPO filters are applied to model hysteresis characteristic of Piezoelectric actuator, and the modeling effect is verified via a micro-positioning system experiment platform based on Piezoelectric actuator. Experimental results show that the modified LPO filters can achieve better accurate hysteresis modeling.

こう配法に基づく単独の適応フィルタを用いたアクティブノイズコントロールシステム

An active noise control system using the gradient based adaptive algorithm without a model of the secondary path is proposed. The cost function of this adaptive system is a square sum of the cross-correlation coefficient of the input noise and the output error signal. Importantly, this system is composed of single transversal adaptive filter that estimates the inverse transfer function of the secondary path and the transfer function of the primary path at the same time. A new gradient based adaptive algorithm and its fast version using only the input signal and the output error signal are formulated, then the above mentioned analytical results are verified by computer simulation.

Experiments on resonant vibration suppression of a piezoelectric flexible clamped–clamped plate using filtered-U least mean square algorithm

This article investigates the adaptive filtered-U least mean square feed-forward algorithm for active resonant vibration control of a clamped–clamped flexible piezoelectric plate structure under persistent harmonic excitation. Different from the widely used filtered-X least mean square algorithm based on the finite impulse response filter, the filtered-U least mean square algorithm uses the infinite impulse response filter. An infinite impulse response filter can be constituted simply by using two adaptive transversal filters. The filtered-U least mean square algorithm can model the system accurately with much fewer coefficients. Moreover, the filtered-U least mean square algorithm has better control performance and stability in the presence of vibration control feedback, owing to the inherent zero-pole structure of the infinite impulse response filter. In this investigation, the filtered-U least mean square algorithm is implemented only in experiments. Two experimental cases are carried out, including the reference signal extracted from the function signal generator and the lead zirconate titanate sensor. A proportional–derivative feedback control algorithm is also applied as a comparison. The experimental results demonstrate the feasibility and performance of the designed proportional–derivative controller and filtered-U least mean square controller.

DCD-RLS Adaptive Filters With Penalties for Sparse Identification

In this paper, we propose a family of low-complexity adaptive filtering algorithms based on dichotomous coordinate descent (DCD) iterations for identification of sparse systems. The proposed algorithms are appealing for practical designs as they operate at the bit level, resulting in stable hardware implementations. We introduce a general approach for developing adaptive filters with different penalties and specify it for exponential and sliding window RLS. We then propose low-complexity DCD-based RLS adaptive filters with the lasso, ridge-regression, elastic net, and penalties that attract sparsity. We also propose a simple recursive reweighting of the penalties and incorporate the reweighting into the proposed adaptive algorithms to further improve the performance. For general regressors, the proposed algorithms have a complexity of operations per sample, where is the filter length. For transversal adaptive filters, the algorithms require only operations per sample. A unique feature of the proposed algorithms is that they are well suited for implementation in finite precision, e.g., on FPGAs. We demonstrate by simulation that the proposed algorithms have performance close to the oracle RLS performance.

A variable step-size gradient adaptive lattice algorithm for multiple sinusoidal interference cancelation

Abstract In passive sonar, adaptive algorithms can be used to cancel strong sinusoidal self-interferences. In order to correctly recover low-power target signals during the early stages of processing, these adaptive algorithms must provide fast convergence and, at the same time, narrow notches at the frequencies of the sinusoids. In this respect, the gradient adaptive lattice (GAL) algorithm is a very attractive choice. However, the GAL algorithm with a constant step-size parameter has to compromise between the convergence rate and notch bandwidths. Therefore, in this article, we propose a variable step-size scheme for the GAL algorithm that can achieve both a fast convergence rate and narrow notches. Simulation results demonstrate the efficiency of the proposed algorithm compared to both the conventional GAL algorithm and transversal adaptive filter combined with the variable step-size scheme.

LDPC-Coded Cooperation with Receive Multi-Antenna and Unknown CSI in the Destination

This paper studies a coded cooperation scheme with receive multi-antenna in the destination. A kind of simple-encoding irregular systematic low-density-parity-check (LDPC) codes is applied to the scheme. For Rayleigh block fading channels, in the unknown channel state information scenario, space-based adaptive least-mean square (LMS) transversal filters are adopted in the destination to realize receive diversity gain. The filtered signals from the source and relay are decoded by a joint "Min-Sum" iterative decoding algorithm. This algorithm agrees with the bilayer Tanner graph that can be used to fully characterize two distinct irregular systematic LDPC codes employed by the source and relay. Simulation results verify the effectiveness of the space-based adaptive LMS transversal filters in the coded cooperation scheme. Meanwhile, theoretical analysis and numerical simulation show that the proposed coded cooperation scheme can well combine cooperation diversity, multi-receive diversity and channel coding gains, and clearly outperforms the coded non-cooperation one under the same conditions.

An LDPC coded cooperative MIMO scheme over Rayleigh fading channels with unknown channel state information

This paper describes a coded cooperative multiple-input multiple-output (MIMO) scheme, where structured low-density parity-check (LDPC) codes belonging to a family of repeat-accumulate (RA) codes are employed. The outage probability of the scheme over Rayleigh fading channels is deduced. In an unknown channel state information (CSI) scenario, adaptive transversal filters based on a spatio-temporal recursive least squares (ST-RLS) algorithm are adopted in the destination to realize receive diversity gain. Also, a joint ‘Min-Sum’ iterative decoding is effectively carried out in the destination. Such a decoding algorithm agrees with the bilayer Tanner graph that can be used to fully characterize two distinct structured LDPC codes employed by the source and relay. Simulation results verify the effectiveness of the adopted filter in the coded cooperative MIMO scheme. Theoretical analysis and numerical simulations show that the LDPC coded cooperative MIMO scheme can well combine cooperation diversity, multi-receive diversity, and channel coding gains, and clearly outperforms coded noncooperation schemes under the same conditions.

Análisis matemático al Método D'Hondt de asignación de escaños parlamentarios

El método de D’Hondt, basado en divisiones sucesivas, es utilizado en muchos países para la repartición de escaños al Parlamento. El método presenta dificultades en las asignaciones cuando las cantidades de votos tienen relaciones, entre sí, de 1, 1/2, 1/3, ... , 1/n, o 1,2, 3,... , n donde n es el número máximo de escaños que se disputan. Se demuestra con teorías de continuidad de funciones, geometría analítica y ejemplos, los casos de discontinuidad que afectan de manera importante al método. Estas situaciones se dilucidan a través de sorteos en casos de empate en la asignación de escaños.

Practical adaptive filter controls for precision beam pointing and tracking with jitter attenuation

The imaging, pointing, and tracking performance of precision optical systems are degraded by various disturbances which induce optical beam jitter. The present research proposes adaptive filter control methods for actively attenuating beam jitter using a fast steering mirror. Control loops with various structures of adaptive transversal filters are developed to suppress time-varying or uncertain jitter, and their characteristics and performances are compared. In particular, for situations when obtaining reference signals which are fully coherent with the disturbance is not possible, methods for incorporating multiple semi-coherent reference signals into the control law are developed. An index variable is defined to measure quality of various references signals, and a few signals are selected based on this index. The developed controllers are verified on a jitter control testbed, and experimental results show that the adaptive methods show superior performance in jitter attenuation over the conventional non-adaptive method.

Modeling of hysteresis in piezoelectric actuator based on adaptive filter

A novel adaptive transversal filter modeling is presented for the hysteresis characteristic in PEA (piezoelectric actuator). First, the hysteresis modeling capability of delay operator based adaptive transversal filter is explored. On this basis, delay operators of adaptive transversal filter are replaced with Backlash operators to compose a new serial structure of adaptive transversal filter model, and LMS (least mean square) algorithm is used to adjust the weight values. And then, as LMS algorithm brings a serious confrontation of the convergence speed and steady-state offset, a new improved adaptive method focus on the convergence factor is brought in. The new filter with this improved algorithm makes the contradiction of convergence speed and steady-state offset could be unified to some extent. At last, the two adaptive transversal filters are applied to model for hysteresis characteristic of PEA, and the modeling effect is verified via a micro-positioning system experiment platform based on PEA. Experimental results show that the proposed Backlash operator based adaptive filter can achieve accurate hysteresis modeling, and the effectiveness of the improved adaptive algorithm is also demonstrated.

BPSK Receiver Based on Adaptive Structure with Remodulation

In this paper we propose a binary phase shift keying (BPSK) signal receiver, where the reception is performed by a new complexadaptive structure with remodulation (R-ATF) which does not require the exact knowledge of the carrier frequency. Therefore, thisreceiver does not have a phase-locked loop (PLL), and it has a fixed frequency oscilator with frequency equal to the expected inputsignal frequency. The proposed structure is created by modifying a complex adaptive transversal filter with the introduction of signalremodulation, and it uses least mean squares (LMS) algorithm for its weights adaptation. The main feature of this receiver is that it hasperformances that are close to the performances of the BPSK receiver with an ideal extraction of the reference carrier for a wide rangeof frequency offsets of practical importance between the input signal and the fixed frequency reference carrier in the receiver. Ill. 5, bibl.8 (in English; abstracts in English and Lithuanian).http://dx.doi.org/10.5755/j01.eee.113.7.620

An Improved Computational Model for Adaptive Communication Channel Estimation

Channel estimation is an important and necessary function performed by modern wireless receivers. The goal of channel estimation is to measure the effects of the channel on known or partially known transmission. The usual practice in acquiring knowledge about a channel is to model the channel and then acquire the parameters involved in the model. This paper proposes a variable partial update model for adaptive communication channel estimation with a view to improving signal error at the receiver station. The proposed model is composed of finite impulse response transversal adaptive filter and least mean square adaptation algorithm. The performance of the proposed model was compared with the full update model. The evaluation results indicated that the proposed model performed better than the full update model in terms of computational complexity, memory load, and convergence rate.

A Lattice Transversal Joint Adaptive Filter with Fixed Reflection Coefficients

We present a lattice transversal joint (LTJ) adaptive filter with fixed reflection coefficients to achieve fast convergence with low complexity. The reflection coefficients of the filter are given by the statistics of speech signals, and the proposed order of the lattice predictor is one. Experimental results confirm that as compared to the adaptive transversal filter, the proposed adaptive filter achieves fast convergence with a negligible increase in complexity. The proposed adaptive filter converges around six times faster than the adaptive transversal filter in case of the band-limited voiced signal from the ITU-T G.168 standard.

A Noise Free Adaptive Pre-inverse System and Its Application to Motor Control

In general, the adaptive system using the structure in which an adaptive filter is placed before the unknown system to estimate the inverse transfer function of the unknown system is called pre-inverse adaptive system. The equalizing type adaptive system that the weights of the adaptive transversal filter inserted after the unknown system are copied to the transversal filter inserted before the system is the representative example. The problem of this system is that the convergence value has the bias error since the adaptive parameters are updated to the direction where the estimation error including the noise was minimized. In this paper we consider a noise free equalizing type adaptive algorithm and its application to the adaptive control of the motor. The convergence of the control system is guaranteed under the assumption of the uncorrelated property of the noise, disturbance and the command input. Finally, these results of theoretical consideration are verified by computer simulation.

Statistical Evaluation of Efficiency of an Adaptive Transversal Filter

Efficiency of an adaptive transversal filter is determined analytically at undetermined weight coefficients. An example of evaluation of the quality of an algorithm of adaptive filtration in a steady-state mode is given.