Adaptive Finite Impulse Response Filter Research Articles

Maximum Complex Correntropy Criterion Adaptive IIR Filtering Based on Gauss-Newton Approach

Adaptive infinite impulse response (IIR) filters have received noticeable consideration for its lower computational complexity compared with adaptive finite impulse response (FIR) filters recently. At present, the adaptive IIR algorithms are almost using the well-established stochastic gradient descent method, but the convergence rate is less than satisfactory. In this paper, to pursue the fast convergence speed of Gauss-Newton (GN) method, we present a GN algorithm for adaptive IIR filters with complex coefficients based on the complex correntropy measure. Besides, the steady-state excess mean square error is provided. Simulations are performed to show the eximious performance of this algorithm.

Adaptive FIR Filter Design with Approximate Adder and Hybridized Multiplier for Efficient Noise Eradication in Sensor Nodes

Finite Impulse Response (FIR) filter contributes a major role in most of the signal processing applications. However, the Finite Impulse Response filter performance is restricted by its speed, power and area usage. To address these issues, an adaptive FIR filter design using approximate adder and Hybridizing (Radix-8 Booth and TRAM) Approximate Multiplier (DA-AFIR-leadx-hybam-AC) is proposed in this manuscript for eradicating the noise in the sensor nodes. Here, Low error together with area efficient approximate adder (leadx) is used for reducing path delay and area utilization. For approximate multiplier design, proposed Hybridizing (Radix-8 Booth and TRAM) Approximate Multiplier using 15–4 Approximate Compressors (hybam-AC) is used for decreasing power consumption and design complexity. The simulation of the proposed model is implemented in Verilog and the design is synthesized in FPGA utilizing Xilinx ISE 14.5. The proposed DA-AFIR-leadx-hybam-AC filter design attains 33.6%, 22.75%, 29.69% lower power and 43.58%, 11.3%, 33.07% lower delay than the existing approaches, like DA-AFIR-MLDA-RNS, DA-AFIR-Hyb-CSD-ABR, DA-AFIR-SOPOT-MPGBP. Finally, the proposed DA-AFIR-leadx-hybam-AC filter design is applied for noise removal application in sensor nodes. The proposed Filter is implemented in MATLAB/Simulink for reading input signal.

Development of an adaptive finite impulse response filter optimization algorithm using rough set theory

Signal processing is crucial that as one sends information, there is a corresponding process to encode, decode, and clean the signal of unwanted noise and disruptions via use of filters. Due to the environment and how unpredictable it can be and how noise can come from almost anywhere, the typical filter to be used are adaptive filters. Adaptive filters are non-linear filters and have been used regularly regarding adaptive signal processing, this means that the filter changes accordingly and adapts to the environmental noise surrounding it. The world today has numerous applications for adaptive filters such as channel equalization and acoustic noise cancellation. This incentivizes the further development of this specific technology and the constant research that is ongoing. The main component when it comes to adaptive filtering is the algorithms used for the filter. This research compares the least mean square (LMS) and recursive least square (RLS) algorithms concerning their effectiveness in filtering out unwanted acoustic noises. The paper will cover the design and implementation of an optimized rough set based adaptive finite impulse response (FIR) filter for acoustic noise cancellation. The microstrip and bowtie antenna were used to relay the data. The software MATLAB was used for the simulation.

A capacitance sensing method with trans-impedance based readout circuit and adaptive filtering for micro-gyro

Trans-impedance amplifier (TIA) based capacitance–voltage (C–V) readout circuit is an attractive choice for micro-machined gyroscope for its simplicity and superior performance. In this work, the noise and the C–V gain characteristics of the TIA circuit are analyzed in detail. Then, a TIA based readout circuit with a C–V gain of about 286 dB is designed, and a series of experiments are conducted to test the performance of the circuit. Both the analysis and test results show that T-network TIA should be avoided as far as possible for its poor noise performance. All results also show that there is a signal-to-noise ratio (SNR) limit for the TIA based readout circuit, and the SNR can only be further improved by filtering. Hence, an adaptive finite impulse response filter is designed to further improve the SNR of the sensed signal. For a gyroscope with a peak-to-peak variable capacitance of about 200 aF, a SNR of 22.8 dB can be achieved by the designed circuit and a SNR of 47 dB can be obtained by further adaptive filtering. Finally, the solution presented in this paper achieves a capacitive sensing resolution of 0.9 aF.

Development of a design optimization algorithm for a bowtie antenna

A bowtie antenna is one of the simple dipole antennas with an omnidirectional pattern utilized in several applications. It is used in industrial applications, scientific applications, and medical applications. Its elementary design can be subjected to modification to expand the applications of the dipole and improve its performance. This paper aims to develop a design optimization algorithm for a bowtie antenna with an adaptive finite impulse response (FIR) filter. In the paper, the different designs of the bowtie antenna are simulated using MATLAB software. The design of antennas is constructed using the partial differential equation (PDE) toolbox in MATLAB software. The designs explored in the paper are the slotted microstrip bowtie antenna and the double flare bowtie antenna. A traditional bowtie was also simulated to be used as a reference for the evaluation of the modified antennas. The dimensions of the designs are kept closely like draw accurate conclusions about the effects of the refinements done. The effects of the modification of the designs on the directivity and return loss are determined to assess the effectiveness of the design alterations.

Simulations on the effects of an optimized bowtie dipole antenna with an adaptive FIR filter

In the evolution of technology through the years, antennas are use in varying wireless systems have been in demand. Antennas play a great role in transmitting and receiving signals. As its application is heavily used in many days to day activities, it is important to create a cost-efficient and quick way to analyze its performance, characteristics, and relationship to different variables. As many radiation pattern acquisition devices are expensive, this simulation proposes a quick, reliable, and cost-friendly way to simulate 2D patterns in the E-plane and H-plane of a bowtie dipole antenna with an adaptive finite impulse response (FIR) filter. Through this study, the software MATLAB will be utilized to successfully simulate the radiation patterns of antennas with varying lengths. With the use of MATLAB toolboxes, the researchers aim to be able to compare different antenna lengths and determine the relationship and effect of it in the obtained 2D radiation pattern. If this method is successful various antenna applications may be implemented in the future with the use of 2D radiation pattern results.

Simultaneous micropositioning and microvibration control of a magnetostrictive Stewart platform with synthesized strategy

In this paper, we present a hybrid adaptive feedforward and feedback controller with hysteresis compensator on a magnetostrictive-actuated multi degree of freedom (DOF) positioning and vibration isolation integrated system (PVIIS). The PVIIS is custom-developed and based on “cubic” Stewart configuration. It is challenging to develop an effective controller to systematically address the issues of cross-coupling, strut hysteresis and dynamics for the PVIIS. Magnetostrictive asymmetric hysteresis leads to the loss of closed-loop output performance with conventional linear controller. To this end, a novel comprehensive controller is proposed in this paper. With the inverse kinematics analysis, the spatial motion of the mobile plate of the PVIIS is decoupled into the independent motions of six actuator struts. As for controlling the single strut of the PVIIS, the hybrid adaptive feedforward (AFF) and proportional–integral–derivative (PID) feedback controller with asymmetric hysteresis compensator (HC) is constructed. Among them, the AFF sub-controller is characterized by an adaptive finite impulse response (FIR) filter whose coefficients are updated by normalized least-mean squares (NLMS) algorithm. The PID feedback sub-controller is introduced to enhance the ability of positioning and vibration isolation. The arctangent-polynomial modified Prandtl–Ishlinskii (APMPI) model is used to build the inversion-based asymmetric hysteresis compensator. The experimental set-up is built. The positioning and vibration isolation experiments are conducted. Experimental studies show that the output performances are best with the proposed controller compared against sole AFF, hybrid AFF and PID controllers. With the proposed controller, the relative positioning error can maintain around 2.83% when the PVIIS performs 2-DOF rotation in the presence of 0.5 Hz disturbance.

Inverse transfer function identification for high-frequency pressure probes using M-sequence pressure generators

Accurate unsteady pressure measurement is important for the development and improvement of turbomachinery. The miniature pressure probe can adapt to the accurate measurement of pressure in a tight space under harsh working conditions, but the presence of the pressure transmission line makes the probe frequency response characteristics poor, and even causes the pressure signal to be distorted. In this paper, a novel Maximum-length sequence (M-sequence) pressure generator was developed, which generated pulsating pressure signals with wide frequency range and large amplitude pressure fluctuations at a fixed speed, and a time-domain parametric probe inverse transfer function identification method based on finite impulse response (FIR) adaptive filter using the generator was proposed. Four probes with different geometric parameters were fabricated. The probe inverse transfer function obtained by the FIR adaptive filter was compared with that obtained by the traditional non-parametric method to verify the accuracy of the identification method. The pressure at the pressure tap of the probes were reconstructed from the pressure measured by the probe and the inverse transfer function, which was in good agreement with the pressure measured by the reference sensor.

Adaptive Filter based on Absolute Average Error Adaptive Algorithm for Modeling System

Adaptive identification of the bandpass finite impulse response (FIR) filtering system is proposed through this paper using variable step-size least mean square (VSS-LMS) algorithm called absolute average error-based adjusted step-size LMS as an adapted algorithm. This algorithm used to design an adaptive FIR filter by calculating the absolute averaged value for the recently assessed error with the previous one. Then, the step size has been attuned accordingly with consideration of the slick transition of the step size from bigger to smaller to score an achievement through high convergence rate and low steady-state misadjustment over the other algorithms used for the same purpose. The simulation results through the computer demonstrate remarkable performance compared to the traditional algorithm of LMS and another VSS-LMS algorithm (normalized LMS) which used in this paper for the designed filter. The powerful of the filter has been served in the identification system, bandpass filter has been chosen to be identified in the proposed adaptive system identification. It reports conceivable enhancements in the modeling system concerning the time of convergence, which is well-defined as a fast and steady-state adjustment defined with a low level. The designed filter identified the indefinite system with less than 10 samples; meanwhile, other algorithms were taking more than 20 samples for identification. Alongside the fine behavior of preserving the tradeoff between miss adjustment and the capability of tracking, the fewer calculations and computations regarding the algorithm requirement make the applied real-time striking.

Performance Analysis of Orthogonal Gradient Sign Algorithm Using Spline-based Hammerstein Model for Smart Application

This paper presents a spline-based Hammerstein model for adaptive filtering based on a sign algorithm with the normalised orthogonal gradient algorithm. Spline-based Hammerstein architecture consists of an interpolation spline-based adaptive lookup table in the part of nonlinear filter and an adaptive finite impulse response filter used in the part of linear filter. Hammerstein spline adaptive filter (HSAF) is a nonlinear filter for the nonlinear systems among the advantages in the low computational cost and high performance. An adaptive lookup table and spline control points are determined and derived with the orthogonal gradient-based mechanism. Performance analysis in terms of convergence properties and mean square analysis based on the mean square error (MSE) constraint are proven by using the Taylor series expansion of the estimation error in the form of the excess MSE. Experimental results indicate the robust performance of the proposed algorithm can provide the better performance than the other models based on the conventional least mean square Hammerstein spline adaptive filtering algorithm.

Design and Latency Analyses of an Enhanced Mixed-Signal Coupling Network With Adaptive Noise Cancellation for Power Over Data Lines

Automotive Ethernet is considered to be the backbone of future in-vehicle data communication. The IEEE 802.3bu standard specifies the use of one unshielded twisted pair of copper cables to simultaneously carry data and energy via Power over Data Lines (PoDL). One main challenge in combined data and energy transfer is the distortion of the data channel due to wideband interference from power signals present in the Automotive environment. This paper proposes the design of a novel enhanced coupling network for PoDL that features a noise cancelling current source controlled by an adaptive finite impulse response (FIR) filter for the active attenuation of interfering power signals. The concept of active attenuation was proven for a resistive network, an average attenuation of 92 dB was measured up to 120 MHz. Further analyses show that the cancellation performance heavily relies on low latency of the active filter. It is derived that the provided attenuation decreases exponentially with the frequency for a given time delay and a novel latency management concept called compressed summation is proposed. The approach maximizes the cancellation performance of the proposed filter architecture by exploiting the knowledge of the ideal filter function and effective latency to define the FIR-filter weights.

WITHDRAWN: Low power implementation of adaptive block FIR filter design using offset binary coding

Abstract This paper presents a power efficient realization of block least mean square (BLMS) algorithm based adaptive finite impulse response filter (ADF) using offset binary coding (OBC). OBC method is one of the area optimization methods of distributed arithmetic (DA). In the DA scheme partial products of the filter are stored in a look-up table (LUT) followed by a shift accumulate unit (SA). The size of the LUT increases exponentially with length of the filter. Using the OBC method, the size of the LUT is reduced. Memory sharing concept is used to design the registers, which are in turn used for input sample generation. A high range of parallelism is included in the architecture that enhances its performance. The adaption delay is decreased by doing parallel LUT update, filtering and weight updation operations. The results prove that the proposed design consumes 42% less power in comparison to the best existing architectural designs.

Fractional LMS and NLMS Algorithms for Line Echo Cancellation

In long haul communication environments, speech data transmission is severely affected by echoes. This phenomenon results in high bit errors as well as in degraded and annoying performance. Traditionally these problems, including hybrid and acoustic echoes, have been controlled through the use of echo suppressors. These suppressors were subsequently replaced by line echo cancellers using adaptive Finite Impulse Response filters. Fractional calculus has been applied successfully for fixed filtering with constant coefficients and in discrete time adaptive filtering that adjusts the weights according to the environment. This paper presents the Fractional Least Mean Square (FLMS) and Fractional Normalized LMS (FNLMS) algorithms for application in echo cancellation. Moreover, the performances of the FLMS and FNLMS are compared with those provided by the standard LMS, NLMS and Block Discrete Fourier Transform solutions. The mean square error criterion is used as the performance comparison criterion for two types of voice signals namely real and synthetic. The simulation results show a performance improvement of about 50% over the traditional counterparts.

A novel pipelined neural FIR architecture for nonlinear adaptive filter

This paper presents a novel adaptive pipelined neural finite impulse response (PNFIR) filter for nonlinear signal processing. Unlike traditional pipelined recurrent neural network (PRNN), each module of the PNFIR filter is a simple architecture that includes a standard FIR filter followed by a nonlinear activation function. The complete design of proposed filter includes two subsections: The nonlinear part consists of neural FIR (NFIR) modules which is interconnected in a chained form and simultaneously executed in a parallel fashion; the linear subsection is a tapped-delay-line (TDL) linear combiner. Based on convex combination architecture, the adaptive algorithm derived from the gradient descent approach is utilized to update weights of the nonlinear and linear parts. Moreover, the analysis of stability conditions and computational complexity is also presented. Numerous simulation experimental results on nonlinear dynamic systems identification, speech signal and chaotic time series prediction show that the proposed PNFIR filter has simpler architecture, faster convergence rate, and lower computation complexity than the PRNN and joint process filter using pipelined feedforward second-order Volterra architecture (JPPSOV).

Combined IIR and FIR Filter for Improved Power Quality of PV Interfaced Utility Grid

For enhancing the power quality (PQ), an adaptive infinite impulse response (IIR) combined with finite impulse response (FIR) control is utilized for a grid connected solar photovoltaic (PV) system. The power obtained from a solar PV array is affected due to the seasonal and diurnal variability of the sun. Moreover, the utility distribution network is relatively weak for the developing and underdeveloped countries, exacerbating PQ deterioration issues. For the improvement in PQ indices, an adaptive combined IIR and FIR filter is utilized here, which exhibits adaptive control capability of the voltage source converter essential for smart grid operations. The major advantage regarding the utilization of adaptive control involves much less sensitivity to quantization errors. This new application of a combined IIR and FIR filter includes the mitigation of harmonics in the grid currents and the grid voltages, thereby improving PQ along with reactive power compensation. Due to a combination of IIR and FIR filters, the filtering is achieved with fewer coefficients, requiring minimum memory (as in the case of IIR filters) along with easy implementation and design capability (in the case of FIR filters). Test cases corroborate satisfactory performance during the weak grid conditions, such as voltage distortion, unbalance, and swell, and experimental results are obtained though assessment on a developed laboratory prototype. The PQ improvement is evident by observing the total harmonics distortion conferring to the IEEE-519-2014 Std.

Distributed adaptive observer‐based output formation‐containment control for heterogeneous multi‐agent systems with unknown inputs

Here, the authors study the distributed time-varying output formation-containment control of heterogeneous multi-agent systems, where multiple targets have heterogeneous dynamics and unknown inputs. A distributed adaptive observer-based output formation-containment controller is proposed. Firstly, consensus-based adaptive finite impulse response filters are established to estimate the unknown inputs and states of the targets. Then, by constructing an augmented system with the centre of the targets' outputs as its output and using the observers, an output regulation-based formation-containment controller is developed to make agents encircle the targets with certain formation. Finally, a simulation example is given to illustrate the effectiveness of the proposed method.

Systolic architecture for adaptive block FIR filter for throughput using distributed arithmetic

In this paper, the design of distributed arithmetic (DA) finite impulse response (FIR) filter using block least mean square algorithm (BLMS) based on systolic array architecture with parallel data processing units is presented. A high level of parallelism is observed in the proposed work, improving the efficiency of variable coefficient FIR structure. The parallel look-up tables (LUT) in combination with the shift accumulator emulate multiply and accumulate operations. In order to reduce the number of clock cycles, B parallel LUTs are used, where B is the coefficient size. The block processing in BLMS Adaptive FIR Filter of block length L gives L times high throughput. This structure accepts block of input samples and generates block of output in each clock cycle. It requires less number of registers for computing filter output response and weight increment vector as memory reuse concept is used for implementing registers. This structure doesn’t require multiplexer. The designed DA based FIR filter is implemented on FPGA. The implementation results shows that the manuscript presents a high speed and low power architecture. The proposed structure provides 17.3 times less power and 9.5 times increase in throughput when compared to existing designs.

VLSI implementation of distributed arithmetic based block adaptive finite impulse response filter

In this paper, an efficient VLSI architecture of distributed arithmetic (DA) based block least mean square (BLMS) adaptive finite impulse response (ADFIR) filter implementation with parallel processing is proposed. In DA scheme, the filter partial products are precomputed and saved in lookup table (LUT) and then by using shift and accumulation operations filtering can be done. To improve the efficiency, a high level of parallelism is incorporated in the design of variable coefficient ADFIR filter. The parallel LUT followed by shift-accumulate operations replaces multiply and accumulate (MAC) operations. By using BLMS algorithm in ADFIR filter with block length P gives P times fast throughput. Since memory reuse concept is used, the design requires less number of registers to calculate output vector and coefficient increment vector. The proposed design is implemented on FPGA. The implementation results indicate that the proposed design is a low power and high speed architecture. The proposed structure provides 47.4% less power and 22.7% less delay when compared to existing designs.

Multi-channel spline adaptive filters for non-linear active noise control

This paper presents a non-linear multi-channel active noise control (ANC) scheme based on a set of adaptive spline filters as the component controllers. An adaptive spline filter comprises an adaptive finite impulse response (FIR) structure, which is followed by an adaptive spline activation function. A suitable learning rule is developed that updates the parameters of the adaptive FIR filter as well as of the adaptive spline function. Bounds on the learning rates for the proposed method are estimated and a detailed analysis on the computational complexity of the proposed scheme is presented. The proposed method is shown to offer good noise mitigation under non-linear ANC scenarios at a significantly lower computational load in comparison with other methods. In addition, due to the adaptive nature of the activation function, the proposed controller can transform itself from a non-linear to a linear one depending on the noise control scenario.

Joint Polarization Tracking and Equalization in Real-Time Coherent Optical Receiver

We experimentally demonstrate a real-time polarization tracking and equalization method based on the state of polarization detection from the adaptive finite impulse response (FIR) filter coefficients in a polarization division multiplexed (PDM) coherent optical communication system. By calculating the variation of the polarization within a time interval, the polarization rotation speed can be evaluated. In a field-programmable gate array (FPGA), a feedback structure for polarization rotation speed detection and FIR coefficients update can be built up. In this feedback structure, the update coefficient of the filter will be adjusted to an optimal value with the change of detection result. The experimental results show that the establishment of this feedback structure improves the polarization tracking ability in the real-time coherent optical receiver.