Showing papers on "Filter design published in 2014"

Discrete Signal Processing on Graphs: Frequency Analysis

Abstract: Signals and datasets that arise in physical and engineering applications, as well as social, genetics, biomolecular, and many other domains, are becoming increasingly larger and more complex. In contrast to traditional time and image signals, data in these domains are supported by arbitrary graphs. Signal processing on graphs extends concepts and techniques from traditional signal processing to data indexed by generic graphs. This paper studies the concepts of low and high frequencies on graphs, and low-, high- and band-pass graph signals and graph filters. In traditional signal processing, these concepts are easily defined because of a natural frequency ordering that has a physical interpretation. For signals residing on graphs, in general, there is no obvious frequency ordering. We propose a definition of total variation for graph signals that naturally leads to a frequency ordering on graphs and defines low-, high-, and band-pass graph signals and filters. We study the design of graph filters with specified frequency response, and illustrate our approach with applications to sensor malfunction detection and data classification.

Reliable Filtering With Strict Dissipativity for T-S Fuzzy Time-Delay Systems

Abstract: In this paper, the problem of reliable filter design with strict dissipativity has been investigated for a class of discrete-time T-S fuzzy time-delay systems. Our attention is focused on the design of a reliable filter to ensure a strictly dissipative performance for the filtering error system. Based on the reciprocally convex approach, firstly, a sufficient condition of reliable dissipativity analysis is proposed for T-S fuzzy systems with time-varying delays and sensor failures. Then, a reliable filter with strict dissipativity is designed by solving a convex optimization problem, which can be efficiently solved by standard numerical algorithms. Finally, numerical examples are provided to illustrate the effectiveness of the developed techniques.

On Energy-to-Peak Filtering for Nonuniformly Sampled Nonlinear Systems: A Markovian Jump System Approach

Abstract: This paper focuses on the filter design for nonuniformly sampled nonlinear systems which can be approximated by Takagi-Sugeno (T-S) fuzzy systems. The sampling periods of the measurements are time varying, and the nonuniform observations of the outputs are modeled by a homogenous Markov chain. A mode-dependent estimator with a fast sampling frequency is proposed such that the estimation can track the signal to be estimated with the nonuniformly sampled outputs. The nonlinear systems are discretized with the fast sampling period. By using an augmentation technique, the corresponding stochastic estimation error system is obtained. By studying the stochastic stability and the energy-to-peak performance of the estimation error system, we derive the linear-matrix-inequality-based sufficient conditions. The parameters of the mode-dependent estimator can be calculated by using the proposed iterative algorithm. Two examples are used to demonstrate the design procedure and the efficacy of the proposed design method.

Nonfragile $H_{\infty}$ Filter Design for T–S Fuzzy Systems in Standard Form

Abstract: This paper is concerned with the problem of nonfragile H∞ filtering for continuous-time Takagi-Sugeno (T-S) fuzzy systems. The filter to be designed is assumed to have two types of multiplicative gain variations. First, two relaxed H∞ filtering analysis conditions are proposed based on useful linear matrix inequality preliminaries. Whereafter, the results are exploited to derive sufficient conditions for designing a nonfragile H∞ filter, which guarantees a prescribed H∞ performance of the filtering error system. Compared with the existing results, the proposed design methods not only suit for a standard form of the fuzzy filter but also give more relaxed design conditions. Finally, simulation examples will be given to show the efficiency of the proposed design methods.

A Novel Design and Optimization Method of an $LCL$ Filter for a Shunt Active Power Filter

Abstract: Compared with the L filter, the LCL filter is more suitable for high-power low-switching-frequency applications due to its better attenuation characteristics on high frequencies. However, the parameter design for the LCL filter is more complex since both the inhibiting effect of the high-frequency harmonic current and the influence to the controller response performance of the converter should be considered. In this paper, the model of the LCL filter and the design criteria of the LCL filter for a shunt active power filter (SAPF) are analyzed in the beginning. Then, the impacts of all parameters of the LCL filter on SAPF are intuitively drawn on a graph by theoretical derivation. Finally, a novel parameter design and optimization method for the LCL filter is proposed. The validity and effectiveness of the proposed method are proved by simulated and experimental results of a single-phase SAPF prototype at the end of this paper.

Distributed Fault Detection and Isolation Filter Design for a Network of Heterogeneous Multiagent Systems

Abstract: In this brief a distributed fault detection and isolation (FDI) methodology for a network of heterogeneous multiagent systems with different dynamics and order from one another is proposed. An FDI filter is designed such that the effects of disturbances and control inputs on the residual signals are minimized (for accomplishing the fault detection task) subject to the constraint that the transfer matrix function from the faults to the residuals is equal to a preassigned diagonal transfer matrix (for accomplishing the fault isolation task). Moreover, by utilizing the proposed methodology, isolation of simultaneous occurring faults can also be handled. Sufficient conditions for solvability of the problem are obtained in terms of linear matrix inequality (LMI) feasibility conditions. The extended LMI characterization is then used to reduce the conservativeness of the solution by eliminating the couplings between the Lyapunov matrices and the agents' matrices. Simulation results presented demonstrate the effectiveness and capabilities of our proposed design methodology.

Efficient FPGA and ASIC Realizations of a DA-Based Reconfigurable FIR Digital Filter

Abstract: This brief presents efficient distributed arithmetic (DA)-based approaches for high-throughput reconfigurable implementation of finite-impulse response (FIR) filters whose filter coefficients change during runtime. Conventionally, for reconfigurable DA-based implementation of FIR filter, the lookup tables (LUTs) are required to be implemented in RAM and the RAM-based LUT is found to be costly for ASIC implementation. Therefore, a shared-LUT design is proposed to realize the DA computation. Instead of using separate registers to store the possible results of partial inner products for DA processing of different bit positions, registers are shared by the DA units for bit slices of different weightage. The proposed design has nearly 68% and 58% less area-delay product and 78% and 59% less energy per sample than the DA-based systolic structure and the carry save adder (CSA)-based structure, respectively, for the ASIC implementation. A distributed-RAM-based design is also proposed for the field-programmable gate array (FPGA) implementation of the reconfigurable FIR filter, which supports up to 91 MHz input sampling frequency and offers 54% and 29% less the number of slices than the systolic structure and the CSA-based structure, respectively, when implemented in the Xilinx Virtex-5 FPGA device (XC5VSX95T-1FF1136).

Modeling, Analysis, and Design of Multifunction Grid-Interfaced Inverters With Output LCL Filter

Abstract: The purpose of this paper is to investigate the model, control, and implementation of a multifunction grid-interfaced inverter with output LCL filter, which can provide high performance active power current and compensate the existent harmonics simultaneously in a distributed network. Equipped with LCL filter, the proposed multifunction inverter offers reduced switching harmonics and superior output current shapes. However, the multifunction inverter with output LCL filter brings some challenges, including LCL resonance, phase lag, and complexity in system design. To address these issues, this paper analyzes and develops general Thevenin/Norton models for the multifunction grid inverters with LCL filter. Based on the general models of system, this paper presents guidelines of the control and the procedure of filter design for this application. In particular, a proportional-resonant (PR) plus odd-harmonic repetitive control (OHRC) scheme is designed for the outer current loop. The phase compensation method and detailed design criteria for the proposed control scheme are presented. Furthermore, the proposed OHRC scheme is compared with the previous multiple resonant control (MRC) based on their internal relationship. Simulation and experimental results are provided to validate the effectiveness and advantages of the proposed control strategy.

$M$ -Channel Oversampled Graph Filter Banks

Abstract: This paper proposes $M$ -channel oversampled filter banks for graph signals. The filter set satisfies the perfect reconstruction condition. A method of designing oversampled graph filter banks is presented that allows us to design filters with arbitrary parameters, unlike the conventional critically sampled graph filter banks. The oversampled graph Laplacian matrix is also introduced with a discussion of the entire redundancy of the oversampled graph signal processing system. The practical performance of the proposed filter banks is validated through graph signal denoising experiments.

Networked Strong Tracking Filtering with Multiple Packet Dropouts: Algorithms and Applications

Abstract: This paper focuses on the design problem of a recursive networked strong tracking filter (NSTF) for a class of nonlinear networked systems with parameter perturbations and unknown inputs. The sensors for the networked system are allowed to be spatially distributed in a large geographical area, and signals are transmitted via a shared communication channel with limited capacity. For this kind of system structure, the measurements from different sensors may experience probabilistic data loss with different probabilities. A series of Bernoulli sequences is employed to describe the multiple packet dropout rates. Parameter perturbations and unknown inputs in the system are considered in the filter design process. A recursive networked extended Kalman filter is first derived in the least mean square sense by taking the packet dropout phenomenon into account. Then, a fading factor is introduced in the filter structure in order to cope with the parameter perturbations and unknown system inputs, and a recursive NSTF is derived by developing the so-called networked orthogonal principle. It is shown that the proposed NSTF is capable of providing satisfactory estimation results even in the presence of system parameter perturbations and/or unknown system inputs. A simulation study is carried out on a practical Internet-based three-tank system, and the estimation results show the effectiveness and applicability of the proposed filtering techniques.

Event triggered robust filter design for discrete-time systems

Abstract: This study introduces a general event triggered framework of state estimation for discrete-time systems with parameter uncertainties residing in a polytope. A robust filter is designed to ensure the l2 stability from disturbance to the estimation error and to minimise the l2 gain subject to both packet rate and size constraints. The number of data transmission and the data size are reduced by the utilisation of an event detector and a logarithmic quantiser, respectively. The event detector compares the current output measurement with the last transmitted measurement: if the difference is beyond a prescribed percentage of the current measurement, then the current measurement is transmitted to the quantiser. The quantiser encodes the measurement before sending to the filter via a digital communication channel. Conditions for filter design are found using polynomially parameter-dependent Lyapunov functions, which generalise the results using quadratic and linearly parameter-dependent Lyapunov functions. The usefulness of the techniques is demonstrated with an illustrative example.

Observer-based state-space current control for a three-phase grid-connected converter equipped with an LCL filter

Abstract: This paper presents a state-space current control method for active damping of the resonance frequency of the LCL filter and setting the dominant dynamics of the converter current through direct pole placement. A state observer is used, where upon additional sensors are not needed in comparison with the conventional L filter design. The relationship between the system delay and instability caused by the resonance phenomenon is considered. Nyquist diagrams are used to examine the parameter sensitivity of the proposed method. The method is validated with simulations and experiments.

A Frequency-Locked-Loop Filter for Biased Multi-Sinusoidal Estimation

Abstract: In this paper, an adaptive filter, based on a third-order generalized integrator, is proposed to estimate all the parameters of a biased sinusoid The averaging theory is used to prove that the filter identifies the unknown frequency of the signal, in the case of a pure biased sinusoid in input Moreover, in the case of a generic periodic signal, the method provides an estimate of the fundamental frequency by converging to a limit cycle in its vicinity The robustness of the proposed approach with respect to noise in the input signal is analyzed A filter bank is also presented to deal with the reconstruction problem of a generic multi-sinusoidal signal Simulation results are also provided to compare the performances of the method with existing ones

Analysis and Design of a High-Order Discrete-Time Passive IIR Low-Pass Filter

Abstract: In this paper, we propose a discrete-time IIR low-pass filter that achieves a high-order of filtering through a charge-sharing rotation. Its sampling rate is then multiplied through pipelining. The first stage of the filter can operate in either a voltage-sampling or charge-sampling mode. It uses switches, capacitors and a simple gm-cell, rather than opamps, thus being compatible with digital nanoscale technology. In the voltage-sampling mode, the gm-cell is bypassed so the filter is fully passive. A 7th-order filter prototype operating at 800 MS/s sampling rate is implemented in TSMC 65 nm CMOS. Bandwidth of this filter is programmable between 400 kHz to 30 MHz with 100 dB maximum stop-band rejection. Its IIP3 is +21 dBm and the averaged spot noise is 4.57 nV/$surd$ Hz. It consumes 2 mW at 1.2 V and occupies 0.42 mm 2.

Filter chains with associated multipath views for exploring large data sets

Abstract: A multipath explorer may allow a user to quickly visualize an entire population of data hierarchically in a tree-like structure. For example, a user can select a first filter to be applied to a data set, and the multipath explorer can display data in the data set that satisfies the first filter requirements and data in the data set that does not satisfy the first filter requirements. A second filter can be applied to the data in the data set, and the multipath explorer can display data in the data set that satisfies the first and second filter requirements, data in the data set that satisfies the first filter requirements and not the second filter requirements, data in the data set that satisfies the second filter requirements and not the first filter requirements, and data in the data set that does not satisfy the first or second filter requirements.

Analysis and Modeling of a Gain-Boosted N-Path Switched-Capacitor Bandpass Filter

Abstract: The demand of highly-integrated multi-band transceivers has driven the development of blocker-tolerant software-defined radios that can avoid the cost (and loss) of the baluns and SAW filters [1, 2, 3].

An informed parametric spatial filter based on instantaneous direction-of-arrival estimates

Abstract: Extracting desired source signals in noisy and reverberant environments is required in many hands-free communication systems. In practical situations, where the position and number of active sources may be unknown and time-varying, conventional implementations of spatial filters do not provide sufficiently good performance. Recently, informed spatial filters have been introduced that incorporate almost instantaneous parametric information on the sound field, thereby enabling adaptation to new acoustic conditions and moving sources. In this contribution, we propose a spatial filter which generalizes the recently proposed informed linearly constrained minimum variance filter and informed minimum mean square error filter. The proposed filter uses multiple direction-of-arrival estimates and second-order statistics of the noise and diffuse sound. To determine those statistics, an optimal diffuse power estimator is proposed that outperforms state-of-the-art estimators. Extensive performance evaluation demonstrates the effectiveness of the proposed filter in dynamic acoustic conditions. For this purpose, we have considered a challenging scenario which consists of quickly moving sound sources during double-talk. The performance of the proposed spatial filter was evaluated in terms of objective measures including segmental signal-to-reverberation ratio and log spectral distance, and by means of a listening test confirming the objective results.

An FPGA-Based Fully Synchronized Design of a Bilateral Filter for Real-Time Image Denoising

Abstract: In this paper, a detailed description of a synchronous field-programmable gate array implementation of a bilateral filter for image processing is given. The bilateral filter is chosen for one unique reason: It reduces noise while preserving details. The design is described on register-transfer level. The distinctive feature of our design concept consists of changing the clock domain in a manner that kernel-based processing is possible, which means the processing of the entire filter window at one pixel clock cycle. This feature of the kernel-based design is supported by the arrangement of the input data into groups so that the internal clock of the design is a multiple of the pixel clock given by a targeted system. Additionally, by the exploitation of the separability and the symmetry of one filter component, the complexity of the design is widely reduced. Combining these features, the bilateral filter is implemented as a highly parallelized pipeline structure with very economical and effective utilization of dedicated resources. Due to the modularity of the filter design, kernels of different sizes can be implemented with low effort using our design and given instructions for scaling. As the original form of the bilateral filter with no approximations or modifications is implemented, the resulting image quality depends on the chosen filter parameters only. Due to the quantization of the filter coefficients, only negligible quality loss is introduced.

Spectrum splitting metrics and effect of filter characteristics on photovoltaic system performance.

Abstract: During the past few years there has been a significant interest in spectrum splitting systems to increase the overall efficiency of photovoltaic solar energy systems. However, methods for comparing the performance of spectrum splitting systems and the effects of optical spectral filter design on system performance are not well developed. This paper addresses these two areas. The system conversion efficiency is examined in detail and the role of optical spectral filters with respect to the efficiency is developed. A new metric termed the Improvement over Best Bandgap is defined which expresses the efficiency gain of the spectrum splitting system with respect to a similar system that contains the highest constituent single bandgap photovoltaic cell. This parameter indicates the benefit of using the more complex spectrum splitting system with respect to a single bandgap photovoltaic system. Metrics are also provided to assess the performance of experimental spectral filters in different spectrum splitting configurations. The paper concludes by using the methodology to evaluate spectrum splitting systems with different filter configurations and indicates the overall efficiency improvement that is possible with ideal and experimental designs.

Optimal Least-Squares FIR Digital Filters for Compensation of Chromatic Dispersion in Digital Coherent Optical Receivers

Abstract: This paper proposes optimal finite-length impulse response (FIR) digital filters, in the least-squares (LS) sense, for compensation of chromatic dispersion (CD) in digital coherent optical receivers. The proposed filters are based on the convex minimization of the energy of the complex error between the frequency responses of the actual CD compensation filter and the ideal CD compensation filter. The paper utilizes the fact that pulse shaping filters limit the effective bandwidth of the signal. Then, the filter design for CD compensation needs to be performed over a smaller frequency range, as compared to the whole frequency band in the existing CD compensation methods. By means of design examples, we show that our proposed optimal LS FIR CD compensation filters outperform the existing filters in terms of performance, implementation complexity, and delay.

Generalized Method of Wavelet Moments for Inertial Navigation Filter Design

Abstract: The integration of observations issued from a satellite-based system (GNSS) with an inertial navigation system (INS) is usually performed through a Bayesian filter such as the extended Kalman filter (EKF). The task of designing the navigation EKF is strongly related to the inertial sensor error modeling problem. Accelerometers and gyroscopes may be corrupted by random errors of complex spectral structure. Consequently, identifying correct error-state parameters in the INS/GNSS EKF becomes difficult when several stochastic processes are superposed. In such situations, classical approaches like the Allan variance (AV) or power spectral density (PSD) analysis fail due to the difficulty of separating the error processes in the spectral domain. For this purpose, we propose applying a recently developed estimator based on the generalized method of wavelet moments (GMWM), which was proven to be consistent and asymptotically normally distributed. The GMWM estimator matches theoretical and sample-based wavelet variances (WVs), and can be computed using the method of indirect inference. This article mainly focuses on the implementation aspects related to the GMWM, and its integration within a general navigation filter alibration procedure. Regarding this, we apply the GMWM on error signals issued from MEMS-based inertial sensors by building and estimating composite stochastic processes for which classical methods cannot be used. In a first stage, we validate the resulting models using AV and PSD analyses and then, in a second stage, we study the impact of the resulting stochastic models design in terms of positioning accuracy using an emulated scenario with statically observed error signatures. We demonstrate that the GMWM-based calibration framework enables to estimate complex stochastic models in terms of the resulting navigation accuracy that are relevant for the observed structure of errors.