The authors develop an analytical technique for the design of centrosymmetric two-dimensional FIR (finite impulse response) filters by formulating a frequency-domain least-square approximation problem. A study of some...
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The authors develop an analytical technique for the design of centrosymmetric two-dimensional FIR (finite impulse response) filters by formulating a frequency-domain least-square approximation problem. A study of some of the properties of the matrices involved in this design problem leads to an optimal analytical solution for the filter co-efficients. This solution permits fast calculation of the coefficients directly from the given frequency-response specifications without requiring either optimization procedures or matrix inversion operations. It is shown through design examples that the design time and computational complexity using the proposed technique are significantly lower than those for the usual optimization techniques.< >
An adaptive two-stage scheme for a synchronous, two-user CDMA environment with unknown received signal energies is presented. It consists of a tandem of the matched filter front-end followed by the interference cancel...
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An adaptive two-stage scheme for a synchronous, two-user CDMA environment with unknown received signal energies is presented. It consists of a tandem of the matched filter front-end followed by the interference canceler whose weights are adjusted by an adaptive algorithm. The error probability was evaluated analytically, and it was shown that the receiver provides satisfactory performance in the near-far scenarios.< >
It is demonstrated that the performance of a satellite network can be optimized by changing its facilities. A mesh-connected, circuit-switched satellite communication network is shown to perform better by adaptively r...
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It is demonstrated that the performance of a satellite network can be optimized by changing its facilities. A mesh-connected, circuit-switched satellite communication network is shown to perform better by adaptively reconfiguring the network by using simulated annealing to suit the current traffic conditions. Proper allocation of link capacities and placing an optimal reservation scheme for the network are crucial in this scheme. Routing is performed dynamically. Simulation results confirm these characteristics.< >
Adaptive, in-call, bandwidth reservation may be used to enhance bandwidth utilization in a policed ATM virtual path shared by traffic streams originated by many bursty sources. The mechanism is found to be effective w...
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Adaptive, in-call, bandwidth reservation may be used to enhance bandwidth utilization in a policed ATM virtual path shared by traffic streams originated by many bursty sources. The mechanism is found to be effective when large changes in the aggregate traffic rate are slow in comparison to the feedback delay with which a requested change in the reserved rate is obtained. We present a model, based on Markov-modulated sources and stochastic fluid methods, for performance analysis of the proposed mechanism. The model, corroborated by simulations, is used to study the effects of feedback delay.< >
The authors consider the synthesis problem of a traffic control scheme based on conservation laws. They derive a conservation law for cell loss probabilities, for an ATM (asynchronous transfer mode) node with a finite...
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The authors consider the synthesis problem of a traffic control scheme based on conservation laws. They derive a conservation law for cell loss probabilities, for an ATM (asynchronous transfer mode) node with a finite buffer size and correlated arrival processes. Based on this law, they develop a buffer allocation (i.e., pushout) algorithm that meets a prespecified cell loss objective, if it can be satisfied, or treats the traffic classes "fairly", if it cannot. The algorithm is dynamic and requires no knowledge of arrival statistics.< >
A class of nonlinear adaptive filters called generalized adaptive neural filters (GANFs) developed to generalize stack filters to a larger class of nonlinear filters and to outperform stack filters is discussed. They ...
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A class of nonlinear adaptive filters called generalized adaptive neural filters (GANFs) developed to generalize stack filters to a larger class of nonlinear filters and to outperform stack filters is discussed. They are based on the theory of stack filters and neural networks. It is shown that GANFs have better noise suppression performance than stack filters. The implementation of GANFs is discussed, and the theoretical analysis in regards to the performance of GANFs on EKG signalprocessing is also presented.< >
Priority shaping of aggregate source traffic is proposed for use with policed virtual paths in asynchronous transfer mode (ATM) networks. The shaping function, located between the traffic sources sharing the path and ...
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Priority shaping of aggregate source traffic is proposed for use with policed virtual paths in asynchronous transfer mode (ATM) networks. The shaping function, located between the traffic sources sharing the path and the network edge, acts as a self-policing mechanism augmented by a form of priority service to assure satisfactory levels of cell loss and delay for traffic streams with differing service requirements multiplexed into a single virtual path. Two versions of the shape are proposed, and their interaction with a virtual path policed by a leaky-bucket mechanism is discussed. The problem of optimization of shaper design parameters is considered.< >
The generalized adaptive neural filter (GANF) is a new type of adaptable filter. The GANF relies upon neural functions to set up a filtering operation. The authors study a few of the possible neural networks which can...
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The generalized adaptive neural filter (GANF) is a new type of adaptable filter. The GANF relies upon neural functions to set up a filtering operation. The authors study a few of the possible neural networks which can be used in a GANF. The capabilities of the neural nets are examined and the filtering abilities of the GANF are obtained through simulation. While the GANF structure used is somewhat simplified, the filter is also compared with other nonadaptive filters. These filters provide a reference so that relative performance can be more realistically judged.< >
It is shown how the total least squares recursive algorithm for the real data FIR (finite impulse response) adaptive filtering problem can be applied to reconstruct a high-resolution filtered image from undersampled, ...
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It is shown how the total least squares recursive algorithm for the real data FIR (finite impulse response) adaptive filtering problem can be applied to reconstruct a high-resolution filtered image from undersampled, noisy multiframes, when the interframe displacements are not accurately known. This is done in the wavenumber domain after transforming the complex data problem to an equivalent real data problem, to which the algorithm developed by C.E. Davila (Proc. ICASSP 1991 p.1853-6 of 1991) applies. The procedure developed also applies when the multiframes are degraded by linear shift-invariant blurs. All the advantages of implementation via massively parallel computational architecture apply. The performance of the algorithm is verified by computer simulations.< >
To obtain large speed-up factors in Monte Carlo simulation using importance sampling (IS), the modification, or bias of the underlying probability measures must be carefully chosen. Analytical optimization techniques ...
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To obtain large speed-up factors in Monte Carlo simulation using importance sampling (IS), the modification, or bias of the underlying probability measures must be carefully chosen. Analytical optimization techniques are generally ineffective, especially for queueing networks with bursty traffic. The authors present two stochastic gradient optimization techniques that lead to favorable IS parameter settings in the simulation of queueing networks, including queues with bursty traffic. Namely, they motivate and describe the stochastic gradient descent (SGD) algorithm, and the stochastic (important event) frequency ascent (SFA) algorithm. They demonstrate the effectiveness of their algorithms by applying them to the problem of estimating the blocking probability for a queue with two arrival streams, a modified interrupted Bernoulli stream and a Markov modulated Bernoulli stream with batch arrivals, deterministic service times, and finite capacity K (denoted by M-IBP+MMBBP/D/1/K). Speed-up factors of 1 to 6 orders of magnitude over conventional Monte Carlo simulation are achieved for the examples presented.< >
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