A polynomial filtering algorithm is designed for estimating a Markov sequence with the use of linear measurements. The feature of the estimation problem is that the Markov sequence is described by a nonlinear shaping ...
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ISBN:
(数字)9783907144022
ISBN:
(纸本)9781728188133
A polynomial filtering algorithm is designed for estimating a Markov sequence with the use of linear measurements. The feature of the estimation problem is that the Markov sequence is described by a nonlinear shaping filter, which is a second-order polynomial with respect to the state vector components. The efficiency of the proposed algorithm is analyzed in comparison with the nonlinear optimal algorithm and an extended Kalman filter, when solving the problem of gyroscope drift model identification.
Tensor tomography is being investigated as a technique for reconstruction of in vivo tensor fields which will enable development of more accurate models of the properties of biological tissue. This paper presents back...
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Tensor tomography is being investigated as a technique for reconstruction of in vivo tensor fields which will enable development of more accurate models of the properties of biological tissue. This paper presents backprojection filtering algorithms for reconstructing three-dimensional vector and second order tensor fields with the property of being independent of the coordinate z. The backprojection of a complete set of directional projection measurements gives straightforward results that are fairly simple extensions of the usual scalar reconstruction methods. Both vector fields and tensor fields are represented as a sum of solenoidal and irrotational components. The irrotational component of the vector field can be reconstructed from a single set of directional measurements. The reconstruction of the solenoidal and irrotational components for a tensor field each require six directional projection measurements. Results of computer simulations that demonstrate the validity of the mathematical formulations are presented. A simulated cardiac diffusion tensor field shows that the principal component of the tensor field could be specified utilizing half of the number of MRI measurements that are presently being utilized.
The necessary and sufficient conditions for the almost sure convergence of adaptive filtering algorithms based on (a/n) stepsize are established. Assuming that the covariance of the output signal (Y/sub n/) and the cr...
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ISBN:
(纸本)0780304500
The necessary and sufficient conditions for the almost sure convergence of adaptive filtering algorithms based on (a/n) stepsize are established. Assuming that the covariance of the output signal (Y/sub n/) and the cross-covariance of (Y/sub n/) and the reference signal ( psi /sub n/) are constant, if (Y/sub n/ Y/sub n/') satisfies a law of large numbers (where ' denotes transpose), then the necessary and sufficient condition for almost sure convergence of adaptive filtering algorithms is that (Y/sub n/ psi /sub n/') also satisfies the law of large numbers. Moreover when there exists a small deviation from the law of large numbers for (Y/sub n/ Y/sub n/') and (Y/sub n/ psi /sub n/'), there is also a bounded deviation dependent on the former from the convergence of the algorithms, and the latter tends to zero as the former goes to zero.< >
This paper provides a technique to derive a new set of fast Finite Impulse Response (FIR) filtering algorithms founded on the combination of filtering algorithms based on short FFT and short length fast FIR filtering ...
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This paper provides a technique to derive a new set of fast Finite Impulse Response (FIR) filtering algorithms founded on the combination of filtering algorithms based on short FFT and short length fast FIR filtering algorithms. Such composite algorithms have the potential to reduce the arithmetic complexity and the characteristic to maintain a low processing delay, independent of the filter length. A methodology for an efficient implementation on the Digital Signal Processor (DSP) of these algorithms is proposed by an optimised structuring and organization of data in memory in order to keep the improvement brought by the reduction of the arithmetic complexity without exceeding the DSP resources such as number of pointers registers and memory. The performance is evaluated in number of machine cycles per point computed. The solution exists to complete the generator code built for the basic algorithms by adding macro-instructions written in a "DSP" assembly code.
The authors present a new derivation of exact least-squares multichannel and multidimensional adaptive algorithms, based on explicitly formulating the problem as a state-space estimation problem and then using differe...
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The authors present a new derivation of exact least-squares multichannel and multidimensional adaptive algorithms, based on explicitly formulating the problem as a state-space estimation problem and then using different square-root versions of the Kalman, Chandrasekhar, and information algorithms. The amount of data to be processed here is usually significantly higher than in the single-channel case, and reducing the computational complexity of the standard multichannel RLS (recursive least square) algorithm is thus of major importance. This reduction is usually achieved by invoking the existing shift structure in the input data. For this purpose, it is shown how to apply the extended Chandrasekhar recursions, with an appropriate choice of the initial covariance matrix, to reduce the computations by an order of magnitude. In multichannel filters, the number of weights in different channels is not necessarily the same. This is illustrated with two examples: a nonlinear Volterra-series filter and a two-dimensional filter. In the former case the number of weights varies among the channels, but in the latter case all channels have the same number of weights.< >
An efficient real-time implementation of digital filtering algorithms using a multiprocessor system in a ring network is investigated. This method is based on a parallel block processing approach, where a continuous s...
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An efficient real-time implementation of digital filtering algorithms using a multiprocessor system in a ring network is investigated. This method is based on a parallel block processing approach, where a continuous supply of input data is divided into blocks and a block is assigned to each processor in rotation. The system is easily expandable and shows a high efficiency even in a large-scale multiprocessing environment. Methods for solving the dependency problems between the processors are also investigated to increase the number of processors which can be used efficiently. Implementation procedures and results for finite impulse response (FIR), recursive, and adaptive filtering algorithms are illustrated. This method has been successfully tested on the SABRINA (Santa Barbara ring network architecture) multiprocessor system developed at the University of California, Santa Barbara, and some experimental results are included.< >
This paper presents a family variable step-size (VSS) affine projection (AP) adaptive filtering algorithms with selective partial updates (SPU). The presented algorithms have good convergence speed, low steady state m...
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ISBN:
(纸本)9781424467600
This paper presents a family variable step-size (VSS) affine projection (AP) adaptive filtering algorithms with selective partial updates (SPU). The presented algorithms have good convergence speed, low steady state mean square error (MSE), and low computational complexity features. We demonstrate the good performance of the proposed algorithms through simulations in system identification and acoustic echo cancellation scenarios.
The role of gradient-based FIR (finite impulse response) and IIR (infinite impulse response) adaptive algorithms as candidates for adapting an active controller for acoustic noise where there is acoustic feedback from...
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The role of gradient-based FIR (finite impulse response) and IIR (infinite impulse response) adaptive algorithms as candidates for adapting an active controller for acoustic noise where there is acoustic feedback from secondary source to detector is examined. It is shown that the use of the common algorithms without modification is equivalent to making some fairly sweeping approximations. Nevertheless, simulations show that such systems may work well, though not necessarily achieving the maximum attenuation available.< >
In this paper, two shunt active filtering algorithms, namely, synchronous detection technique and newly proposed ***ϕ algorithm have been simulated and implemented in hardware and a comparison has been brought out. Th...
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In this paper, two shunt active filtering algorithms, namely, synchronous detection technique and newly proposed ***ϕ algorithm have been simulated and implemented in hardware and a comparison has been brought out. The proposed algorithm is found to work satisfactorily under various system operating conditions. The hardware implementation of both the schemes have been done and the proposed scheme is found to be simple and working satisfactorily.
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