A recursive scheme is derived for calculation of the expansion coefficients of a known system transfer function into a generalized orthonoimal rational basis. The inherent structure of the basis functions leads to a c...
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A recursive scheme is derived for calculation of the expansion coefficients of a known system transfer function into a generalized orthonoimal rational basis. The inherent structure of the basis functions leads to a computationally efficient method, which needs the solution of a low-dimensional Sylvester equation at each step. The method is demonstrated with a brief example. Possible applications are also discussed.
In this paper a new recursive algorithm for searching the global minimizer of a function is proposed when the function is observed with noise. The algorithm is based on switches between the stochastic approximation (S...
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In this paper a new recursive algorithm for searching the global minimizer of a function is proposed when the function is observed with noise. The algorithm is based on switches between the stochastic approximation (SA) and the random search (RS) with stepsizes decreasing as SA develops and as RS takes steps. It is proved that the algorithm a.s. converges to the global minimizer and is asymptotically normal.
The large deviation principle is shown to hold for a class of stochastic recursive algorithms based on a sequence of random variables satisfying an appropriate mixing condition.
The large deviation principle is shown to hold for a class of stochastic recursive algorithms based on a sequence of random variables satisfying an appropriate mixing condition.
This paper deals with some issues involving a parameter estimation approach that yields estimates consistent with the data and the given a priori information. The first part of the paper deals with the relationships b...
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This paper deals with some issues involving a parameter estimation approach that yields estimates consistent with the data and the given a priori information. The first part of the paper deals with the relationships between various noise models and the 'size' of the resulting membership set, the set of parameter estimates consistent with the data and the a priori information. When there is some flexibility about the choice of the noise model, this analysis can be helpful for noise model selection so that the resulting membership set yields a better estimate of the unknown parameter. The second part of the paper presents algorithms for various commonly encountered noise models that have the following properties: (a) they are recursive and easy to implement;and (b) after a finite 'learning period', the estimates provided by these algorithms are guaranteed to be in (or very 'close' to) the membership set. In general, the interpolatory algorithms, that produce an estimate in the membership set, do not possess nice statistical and worst-case properties similar to those of classical approaches such as least mean squares (LMS) and least squares (LS) algorithms. In the third part of the paper, we propose an algorithm that is optimal in a certain worst-case sense but gives an estimate that is in (or is 'close' to) the membership set. Copyright (C) 1996 Elsevier Science Ltd.
A second-order recursive algorithm for adaptive signal processing is proposed, and a similar algorithm is derived for signal subspace tracking. It is shown that the algorithm encompasses both the RLS and the LMS algor...
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A second-order recursive algorithm for adaptive signal processing is proposed, and a similar algorithm is derived for signal subspace tracking. It is shown that the algorithm encompasses both the RLS and the LMS algorithms as special cases. The computational complexity is the same as for the RLS algorithm, but some extra memory storage is required. The associated ordinary differential equation (ODE) for the autoregressive exogenous (ARX) case algorithm is proven to be globally exponentially stable. Furthermore, it is demonstrated that the proposed algorithm has a higher ability to track time-varying signals than has the RLS algorithm. The proposed algorithm especially handles those situations well where there is a simultaneous system change and decrease of signal power.
We present order-recursive structures for implementing the linear decorrelating and linear minimum mean square error (MMSE) detectors in a computationally efficient manner. These infinite memory length, Linear time in...
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We present order-recursive structures for implementing the linear decorrelating and linear minimum mean square error (MMSE) detectors in a computationally efficient manner. These infinite memory length, Linear time invariant, noncausal systems can be approximated by implementing them as K-input K-output finite impulse response (FIR) filters. We developed a linear multiuser receiver architecture called a recursive linear multiuser detector which has lower computational and memory requirements then an equivalent tap delay line FIR filter implementation. We establish the tradeoff between window length and bit error rate and find that relatively small window size yields performance indistinguishable from the ideal decorrelating detector and the ideal MMSE detector.
IFAPT estimates the parameters of piece-wise linear approximation to assumed continuous narrow-band signals. Its simple, recursive nature enables direct interaction with recursive algorithms, such as the Viterbi and t...
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ISBN:
(纸本)0780344081
IFAPT estimates the parameters of piece-wise linear approximation to assumed continuous narrow-band signals. Its simple, recursive nature enables direct interaction with recursive algorithms, such as the Viterbi and the BCJR in the APP SISO module, used for iteratively decoding concatenated codes. An augmented APP (A(2)P(2))-module, containing IFAPT and BCJR algorithms is here applied to iterative decoding serial concatenated convolutional codes under Rayleigh fading conditions, with diversity reception.
In a recent work the authors derived quaternionic recursions for positions, velocities and acceleration components (inertial, Coriolis and centrifugal) of robot links for robots with only revolute joints (Hachicho, et...
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In a recent work the authors derived quaternionic recursions for positions, velocities and acceleration components (inertial, Coriolis and centrifugal) of robot links for robots with only revolute joints (Hachicho, et al., 1998). In the present paper recursions for the general case, i.e. for robots with both revolute and prismatic joints, are developed
In this paper, we study the H ∞ control problem for singularly perturbed systems under imperfect state measurements by using the recursive approach. We construct a controller that guarantees a disturbance attenuation...
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In this paper, we study the H ∞ control problem for singularly perturbed systems under imperfect state measurements by using the recursive approach. We construct a controller that guarantees a disturbance attenuation level larger than a boundary value of the reduced-order slow and fast subsystems when the singular perturbation parameter ε approaches zero. In order to obtain the controller, we must solve the generalized algebraic Riccati equations. The main results in this paper is to propose a new recursive algorithm to solve the generalized algebraic Riccati equations and to find sufficient conditions for the convergence of the proposed algorithm.
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