It has been shown by some researchers that in a problem of weighted least-square (WLS) design of finite-impulse response (FIR) filters, bulk of the design computation is concerned with the evaluation of the inverse of...
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It has been shown by some researchers that in a problem of weighted least-square (WLS) design of finite-impulse response (FIR) filters, bulk of the design computation is concerned with the evaluation of the inverse of a matrix in order to solve a system of equations. In this paper, a new algorithm for the WLS design of FIR filters is presented, in which an iterative procedure is developed for the inversion of the matrix involved in the design. By imposing a mild constraint on the updation factor of the weighting function, the inverse of a matrix is expanded as a convergent power series. By investigating the properties of some of the matrices from the design formulation, a modified version of the series that converges rapidly is then proposed to evaluate the inverse in each iteration. It is shown,that due to the fast convergence of the power series, one needs to evaluate only the first two or three terms of the series except during the initial stages of the iterations, implying that the conventional operation for matrix inversion is simplified significantly.
An iterative adaptive pole placement algorithm is presented. The stability and the convergence of the algorithmare respectively established. Since one-step iterative formulation in computing controller's parameter...
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An iterative adaptive pole placement algorithm is presented. The stability and the convergence of the algorithmare respectively established. Since one-step iterative formulation in computing controller's parameters is used, the on-line computation cost is greatly reduced with respected to the traditional algorithm. The algorithm with the feed-forward can follow arbitrarily bounded output. The algorithm is also extended to multivariate case. Simulation examples show the efficiency and robustness of the algorithm.
This paper presents a novel iterative receiver used to mitigate the impact of impulsive noise (IN) on orthogonal frequency-division multiplexing (OFDM)-based baseband power-line communications. An adaptive threshold i...
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This paper presents a novel iterative receiver used to mitigate the impact of impulsive noise (IN) on orthogonal frequency-division multiplexing (OFDM)-based baseband power-line communications. An adaptive threshold is mathematically derived for the detection of IN under a desired false alarm probability. This detection mechanism is then used to mitigate IN in two stages. Prior to the OFDM demodulation, a pre-IN mitigation block is used to clip the stronger portions of the IN source. This preprocessing significantly reduces the power of the IN spreading into all subcarriers and, thus, facilitates the detection of residual IN in the second stage. After the OFDM demodulation, the proposed receiver iteratively estimates the channel impulse response and reduces IN sources that were not detected by the pre-IN mitigation block. Post-IN mitigation involves the iterative reconstruction of residual IN, which is then subtracted from the received signal. Denoising is also applied to the estimated channel impulse response. Thus, channel estimation and IN mitigation are mutually beneficial. Simulation results confirm that the proposed iterative receiver significantly improves the mean squared error of the channel estimation as well as bit-error rate.
Surface potential-based compact models are an essential link between circuit simulation and technology due to their physical base. Such models are particularly important for the development of devices and circuits bas...
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Surface potential-based compact models are an essential link between circuit simulation and technology due to their physical base. Such models are particularly important for the development of devices and circuits based on new wide-bandgap semiconductors such as silicon carbide (SiC) where additional physical phenomena in comparison to silicon are considered. An efficient computation of the surface potential (Phi(S)) is one of the core components of Phi(S)-based compact models. We developed a fast and robust iterative algorithm for the surface potential, which takes the specific interface trap distribution of SiC-MOSFETs into account. Therefore, a new initial guess is derived, which reduces the number of required iteration steps by 40% in contrast to the common initial guess for silicon devices. Furthermore, different starting equations and types of iteration steps are compared in terms of convergence speed and stability over a wide range of densities of interface traps, technology parameters, and operating conditions.
This paper presents a numerical algorithm based on a variational iterative approximation for the Hamilton-Jacobi-Bellman equation, and a domain decomposition technique based on this algorithm is also studied. The conv...
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This paper presents a numerical algorithm based on a variational iterative approximation for the Hamilton-Jacobi-Bellman equation, and a domain decomposition technique based on this algorithm is also studied. The convergence theorems have been established. Numerical results indicate the efficiency and accuracy of the methods. (C) 2010 Elsevier Ltd. All rights reserved.
Interference alignment (IA) has been shown as an important technique to achieve a linear capacity scaling in wireless communications. However, the IA scheme over finite signaling dimensions for a general multiple-inpu...
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Interference alignment (IA) has been shown as an important technique to achieve a linear capacity scaling in wireless communications. However, the IA scheme over finite signaling dimensions for a general multiple-input-multiple-output (MIMO) X channel is still rarely studied. The main challenge of MIMO X channels is that the two sets of conditions for IA, namely the interference nulling conditions and the rank preservation conditions, get coupled. The usual IA methods for the interference channel and the broadcasting channel cannot be applied anymore. In this paper, we show that the rank preservation conditions can be replaced by a group of specific rank conditions, under which the IA problem is simplified. Then, based on this technique, an iterative algorithm of IA is designed for the MIMO X channel. The algorithm is designed with limited signaling dimensions. From the simulation results, we find that the algorithm has good performances even under limited signal-to-noise ratio.
In this paper, we present some iterative algorithms, mainly Schwarz algorithms, for an implicit two-sided obstacle problem. The monotonic convergence of the algorithms is proved. (C) 2001 Elsevier Science Ltd. All rig...
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In this paper, we present some iterative algorithms, mainly Schwarz algorithms, for an implicit two-sided obstacle problem. The monotonic convergence of the algorithms is proved. (C) 2001 Elsevier Science Ltd. All rights reserved.
The synthesis of strictly positive real H(2) controllers for collocated control of large space structures is addressed. To perform this synthesis, a convex optimization technique has already been developed using linea...
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The synthesis of strictly positive real H(2) controllers for collocated control of large space structures is addressed. To perform this synthesis, a convex optimization technique has already been developed using linear matrix inequalities. This existing technique is based on two design criteria: strict positive realness and the use Of H(2) norm as the criterion for optimization. It adopts a common Lyapunov solution to both of these criteria, which results in undesirable conservatism. To reduce this conservatism, a new synthesis technique based on iterative algorithms that can produce superior, noncommon Lyapunov solutions is proposed. Even if a common Lyapunov solution is infeasible, the proposed technique can yield feasible, strictly positive real H(2) controllers. An illustrated example is included.
This paper is concerned with iterative solutions to the generalized Sylvester matrix equation A1V+A2V+B1W+B2W=E1VF1+E2VF2+C. Two iterative algorithms are presented to obtain the reflexive and Hermitian reflexive solut...
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This paper is concerned with iterative solutions to the generalized Sylvester matrix equation A1V+A2V+B1W+B2W=E1VF1+E2VF2+C. Two iterative algorithms are presented to obtain the reflexive and Hermitian reflexive solutions. With these iterative algorithms, for any initial reflexive and Hermitian reflexive matrices the solutions can be obtained. Some needed lemmas are first stated, then two theorems are stated and proved where the iterative solutions are obtained. Finally, we report two numerical examples to verify the theoretical results.
In this article, some convergence conditions are investigated for the multiple tuning parameters iterative algorithm (MIA) and the single tuning parameter iterative algorithm (SIA), which are proposed to solve the dis...
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In this article, some convergence conditions are investigated for the multiple tuning parameters iterative algorithm (MIA) and the single tuning parameter iterative algorithm (SIA), which are proposed to solve the discrete periodic Lyapunov matrix equations related to discrete-time linear periodic systems. First, when all the tuning parameters are selected in the interval (0, 1] and the initial conditions are arbitrarily given, it is proven that the MIA is convergent if and only if the discrete-time linear periodic system is asymptotically stable. In particular, when the coefficient matrices of the considered matrix equations are nonnegative, it is shown that the convergence rate of the MIA increases with the tuning parameter increases from 0 to 1. Moreover, the above convergence results derived for the MIA are extended to the SIA. Furthermore, the searching interval of the optimal tuning parameter for the SIA to achieve the fastest convergence rate is narrowed. Finally, two numerical examples are provided to demonstrate the correctiveness of the proposed theoretical results.
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