Statistically robust design of linear filter for non-regenerative MIMO relay systems

This paper addresses the robust linear filter design issues for non-regenerative multiple input multiple output （MIMO） relay systems with imperfect channel state information （CSI） in both or partial hops. By considering statistical Kronecker channel model involving channel mean and antenna correlation, the robust linear processing schemes in imperfect CSI scenario for both hops are first derived based on mean squared error （MSE） criterion. In addition to this, the result is also extended to two practical scenarios, i.e. imperfect CSI for relay link with perfect CSI for access link and imperfect CSI for access link with perfect CSI for relay link. Simulation results show that the proposed scheme is capable of mitigating the performance degradation caused by the imperfect CSI.

A NEW ALGORITHM FOR ADAPTIVE LATTICE FILTERAND ITS APPLICATION IN THE SPEECH LINEARPREDICTIVE SYNTHESIS

In this paper, an adaptive line spectral pair filter is derived from an adaptive lattice filter. A least-mean-square(LMS) type adaptive algorithm used to calculate directly the line spectral pair(LSP) coefficients on a stage-by-stage basis is presented. Experimental results show that the algorithm has higher convergence rate and lower misadjustment as compared with the other algorithms. The LSP coefficients calculated by the algorithm have been used to carry out speech linear predictive synthesis, resulting in better results than PARCOR coefficients.

Reduced-order Kalman filtering for state constrained linear systems

This paper aims at solving the state filtering problem for linear systems with state constraints. Three classes of typical state constraints, i.e., linear equality, quadratic equality and inequality, are discussed. By using the linear relationships among different state variables, a reduced-order Kalman filter is derived for the system with linear equality constraints. Afterwards, such a solution is applied to the cases of the quadratic equality constraint and inequality constraints and the two constrained state filtering problems are transformed into two relative constrained optimization problems. Then they are solved by the Lagrangian multiplier and linear matrix inequality techniques, respectively. Finally, two simple tracking examples are provided to illustrate the effectiveness of the reduced-order filters.

The Marginal Rao-Blackwellized Particle Filter for Mixed Linear/Nonlinear State Space Models

In this paper, the marginal Rao-Blackwellized particle filter （MRBPF）, which fuses the Rao-Blackwellized particle filter （RBPF） algorithm and the marginal particle filter （MPF） algorithm, is presented. The state space is divided into linear and non-linear parts, which can be estimated separately by the MPF and the optional Kalman filter. Through simulation in the terrain aided navigation （TAN） domain, it is demonstrated that, compared with the RBPF, the root mean square errors （RMSE） and the error variance of the nonlinear state estimations by the proposed MRBPF are respectively reduced by 29% and 96%, while the unique particle count is increased by 80%. It is also found that the MRBPF has better convergence properties, and analysis has shown that the existing RBPF is nothing more than a special case of the MRBPF.

Comparison of Signal to Noise Ratios by Stochastic Resonance Device and by Optimal Linear Filter

The signal to noise ratio (SNR) obtained by the devices for manifesting stochastic resonance (SR) can be larger than that by the optimal linear filter. The essential reason for this fact is that there is an energy transfer from noise to signal under the SR condition which is absent in the linear case.

Filtering Function Method for the Cauchy Problem of a Semi-Linear Elliptic Equation

A Cauchy problem for the semi-linear elliptic equation is investigated. We use a filtering function method to define a regularization solution for this ill-posed problem. The existence, uniqueness and stability of the regularization solution are proven;a convergence estimate of H?lder type for the regularization method is obtained under the a-priori bound assumption for the exact solution. An iterative scheme is proposed to calculate the regularization solution;some numerical results show that this method works well.

Fault detection filter design for linear discrete time-varying systems with multiplicative noise

The problem of fault detection for linear discrete timevarying systems with multiplicative noise is dealt with.By using an observer-based robust fault detection filter（FDF） as a residual generator,the design of the FDF is formulated in the framework of H ∞ filtering for a class of stochastic time-varying systems.A sufficient condition for the existence of the FDF is derived in terms of a Riccati equation.The determination of the parameter matrices of the filter is converted into a quadratic optimization problem,and an analytical solution of the parameter matrices is obtained by solving the Riccati equation.Numerical examples are given to illustrate the effectiveness of the proposed method.

Network-Based H_∞ Filtering for Linear Systems with Randomly Varying Sensor Delay

An H∞ filter design for linear time delay system with randomly varying sensor delay is investigated.The delay considered here is assumed to satisfy a certain stochastic characteristic.A stochastic variable satisfying Bernoulli random binary distribution is introduced and a new system model is established by employing the measurements with random delay.By using the linear matrix inequality(LMI) technique,sufficient conditions are derived for ensuring the mean-square stochastic stability of the filtering error systems and guaranteeing a prescribed H∞ filtering performance.Finally,a numerical example is given to demonstrate the effectiveness of the proposed approach.

Properties of Gauss-Newton filter in linear cases

This paper presents the derivation of Gauss-Newton filter in linear cases and an analysis of its properties. Based on the minimum variance theorem, the Gauss-Newton filter is constructed and derived, including its state transition equation, observation equation and filtering process. Then, the delicate relationship between the Gauss-Aitken filter and the Kalman filter is discussed and it is verified that without process noise the two filters are equivalent. Finally, some simulations are conducted. The result shows that the Gauss-Aitken filter is superior to the Kalman filter in some aspects.

NOVEL LINEAR TRANSFORMATION SWITCHED-CAPACITOR FILTER DESIGN

This paper presents a novel method that is applied to realize the Linear Transformation(LT)Switched-Capacitor Filter(SCF).It adopts the Voltage Control Voltage Source(VCVS)equalized transfor-mation to revise the original LC ladder filter and induce it into 16 basic sections and then extend the princi-ple of the LT in order to fit active and 3 port networks and give out switched-capacitor circuits corre-sponding to the 16 basic sections,which can realize all four kinds of filters——LP,HP,BP,BS filters.De-signed examples are given here.An Nth order filter only requires N amplifiers and the circuit is insensitive toparasitic capacitances.The experimental results of a 3rd order elliptic LP and a 6th order elliptic BP are giv-en and agree with the theory.

Design of H_∞ robust fault detection filter for nonlinear time-delay systems

In this paper, the robust fault detection filter (RFDF) design problems are studied for nonlinear time-delay systems with unknown inputs. First, a reference residual model is introduced to formulate the RFDF design problem as an H∞ model-matching problem. Then appropriate input/output selection matrices are introduced to extend a performance index to the time-delay systems in time domain. The reference residual model designed according to the performance index is an optimal residual generator, which takes into account the robustness against disturbances and sensitivity to faults simultaneously. Applying robust H∞ optimization control technique, the existence conditions of the RFDF for nonlinear time-delay systems with unknown inputs are presented in terms of linear matrix inequality (LMI) formulation, independently of time delay. An illustrative design example is used to demonstrate the validity and applicability of the proposed approach.

Exponential passive filtering for a class of nonlinear jump systems

The exponential passive filtering problem for a class of nonlinear Markov jump systems with uncertainties and time-delays is studied. The uncertain parameters are assumed unknown but norm bounded, and the nonlinearities satisfy the quadratic condition. Based on the passive filtering theory, the sufficient condition for the existence of the mode-dependent passive filter is given by analyzing the reconstructed observer system. By using the appropriate Lyapnnov-Krasovskii function and applying linear matrix inequalities, the design scheme of the passive filter is derived and described as an optimization one. The presented exponential passive filter makes the error dynamic systems exponentially stochastically stable for all the admissible uncertainties, time-delays and nonlinearities, has the better abilities of state tracking and satisfies the given passive norm index. Simulation results demonstrate the validity of the proposed approach.

A New Design Approach for Nearly Linear Phase Stable IIR Filter using Fractional Derivative

In this paper,a new design method for digital infinite impulse response(IIR)filters with nearly linear-phase response is presented using fractional derivative constraints(FDCs).In the proposed method,design problem of an IIR frlter is constructed as the minimization of phase error between the desired and designed phase response of an allpass filter(APF)such that the designed lowpass filter(LPF)or highpass frlter(HPF)yields less passband(ep),and stopband errors(es)with optimal stopband attenuation(As).In order to have accurate passband(pb)response,FDCs are imposed on appropriate reference frequency,where the optimality of these FDCs are ensured by using a new greedy based sorting mechanism.The simulated results reflect the efficiency of the proposed method in term of improved passband response along with better transition width.However,small reduction in^is observed within the allowable limit,when compared to noin-fractional design approach,but the designed filter remains immune to wordlength(WL)effect.

非定常Stokes/Darcy模型一种新的time filter算法的分析

首先,在非定常Stokes/Darcy模型的线性多步法的一阶θ-格式的基础上,该文结合time filter算法在几乎不增加计算量的情况下有效地将线性多步法的收敛阶由一阶提高到二阶,从而提出一种新的高效数值算法.其次,该文分别对耦合和解耦的线性多步法加time filter算法的稳定性和误差估计进行了理论分析.最后,数值实验进一步展示了耦合和解耦算法的有效性,收敛性和高效性.

Krein space approach to robust H_∞ filtering for linear uncertain systems

A novel Krein space approach to robust H∞ filtering for linear uncertain systems is developed. The parameter uncertainty, entering into both states and measurement equations, satisfies an energy-type constraint. Then a Krein space approach is used to tackle the robust H∞ filtering problem. To this end, a new Krein space formal system is designed according to the original sum quadratic constraint （SQC） without introducing any nonzero factors into it and, consequently, the estimate recursion is obtained through the filter gain in Krein space. Finally, a numerical example is given to demonstrate the effectiveness of the proposed approach.

THE REALIZATION OF LINEAR SHIFT-VARIANT FILTERS THROUGH STATE FEEDBACK

In this paper a new method to realize rational generalized transfer functions of linearshift-variant digital filters through state feedback is presented In some practical applications therequired characteristics of the filter change slowly.Under these circumstances,the proposedmethod is very effective and the resulting filter structure is simple.A numerical example isprovided to show the performance of the method.

Comparative Study of Linear and Non-Linear Controls of Three-Phase Shunt Active Filters for Improving the Quality of Electrical Energy

The aim of this work is to comparatively study two types of control of a three-phase shunt active filter (TSAF) in order to realize a system of depollution of electrical networks so as to improve the quality of electrical energy. We used two TSA control models which differ in the method of disturbed currents detection, one linear and the other non-linear. The results show that the non-linear control method, although with high calculation blocks, gives more promising results than the linear control method. When connecting a non-linear load (televisions, lamps, variable speed drives, etc.) directly to the public distribution network, the non-linear nature of the load causes the source current to be deformed due to the presence of harmonic currents and voltages. These harmonics thus generate a high reactive power, and therefore considerable electrical losses in the network. One of the solutions to reduce losses on the electricity grid is to incorporate an electronic circuit called a filter into the electricity grid. This work carried out a comparative study of two types of control of a three-phase shunt active filter (TSAF) in order to carry out a system for cleaning up electricity networks in order to improve the quality of electrical energy. We used two TSA control models that differ in the method of detecting disturbed currents, one linear and the other non-linear. The results show that the non-linear control method, although with high calculation blocks, gives better results than the linear control method.

Commissioning of TrueBeamTM Medical Linear Accelerator: Quantitative and Qualitative Dosimetric Analysis and Comparison of Flattening Filter (FF) and Flattening Filter Free (FFF) Beam

Motive of the study is to present quantitative and qualitative analysis and comparison of beam data measurement with FF (flattening filter) and FFF (flattening filter free) beam in a Varian TrueBeamTM Medical Linear Accelerator. Critique of beam characterization and evolution of dosimetric properties for 6 MV, 10 MV, 15 MV FF beam and 6 MVFFF, 10 MVFFF FFF beam has been carried out. We performed the comparison of photon beam data for two standard FF photon energy 6 MV, 10 MV verses 6 MVFFF, and 10 MVFFF FFF beam. Determination and comparison of parameter involved PDD (Percentage depth dose), Depth dose profile, Symmetry, Flatness, Quality index, Relative output factor, Penumbra, Transmission factor, DLG (Dosimetric leaf gap), in addition to degree of Un-flatness and off-axis ratio of FFF beam. Outcomes of presenting study had shown that change of various parameters such as Percentage depth dose curves, Shape of the depth dose profile, Transmission, Value of quality index and significant rise in surface dose for FFF in comparison with FF beam. Differences in the output factor at lower and higher field sizes for FFF beam compared to that of FF beam were found. The maximum output factor deviation between 6 MV and 6 MVFFF was found to be 4.55%, whereas in 10 MV and 10 MVFFF was 5.71%. Beam quality TPR20/10 for FFF beam was found to be lesser in magnitude, 5.42% for 6 MVFFF whereas 4.50% for 10 MVFFF compared to 6 MV and 10 MV FF beam respectively. Jaw transmission and interleaf leakage for FFF beam were found to be lesser than FF beam. Also DLG for FFF beam was found to be lesser in magnitude comparable to that of flattened beam. This study is mainly inclined towards evaluation and comparison of the FF and FFF beam. It has been observed that, the outcome of a commissioning beam data generation fully complies with vendor specification and published literature.