A class of non linear discrete time systems which has a continuous-time counterpart and the capability of describing plants having a dynamics which depend upon the operating point is considered. For this class of non ...
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A class of non linear discrete time systems which has a continuous-time counterpart and the capability of describing plants having a dynamics which depend upon the operating point is considered. For this class of non linear discrete time systems, which can be expressed in input-output form, linearizing output feedback control strategies have been developped. adaptive algorithms allowing to directly estimate the controller parameters are proposed. This approach is applied to the adaptive control of a heat exchanger nonlinear model.
A linearly constrained adaptive multichannel filtering algorithm is described which is designed to adjust the filter coefficients, sample by sample, within the prescribed constraints for adaptive noise cancelling purp...
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A linearly constrained adaptive multichannel filtering algorithm is described which is designed to adjust the filter coefficients, sample by sample, within the prescribed constraints for adaptive noise cancelling purposes. This technique is applicable to many array processing problems where in the signal is corrupted by coherent as well as random noise. By minimizing the ℓ 1 norm of the filter output with time-varying convergence functions containing a version of automatic gain control and a stochastic approximation-like sequence of constants, the algorithm is shown capable of suppressing coherent noises while leaving the signal relatively unchanged.
A new class of nonlinear filters called FIR-weighted myriad hybrid (FIR-WMyH) filters was introduced. These filters have a combination structure of linear FIR filters and weighted myriad filter, and can efficiently ut...
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A new class of nonlinear filters called FIR-weighted myriad hybrid (FIR-WMyH) filters was introduced. These filters have a combination structure of linear FIR filters and weighted myriad filter, and can efficiently utilize the special strongpoint of two filters. Through the backpropagation algorithm used in the neural networks, we derive a stochastic gradient-based adaptive algorithm for determining optimal FIR-WMyH filters under the mean square error (MSE) criterion. In two impulsive noise models, the robust performance of this adaptive algorithm is demonstrated through the computer simulation results.
This paper proposes a new version of an adaptive LMS algorithm, based on a modified estimate of the performance function gradients. This modification leads to the GLMS (geometrically median LMS) adaptive algorithm. Th...
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This paper proposes a new version of an adaptive LMS algorithm, based on a modified estimate of the performance function gradients. This modification leads to the GLMS (geometrically median LMS) adaptive algorithm. This algorithm causes smaller gradient noise into an adaptive filter, thus leading to more stable convergence of an adaptive process. This property makes the GLMS algorithm more stable and superior in some applications than the LMS algorithm. The convergence analysis of GLMS algorithm is also performed, and the comparative simulation results (with respect to the LMS algorithm) presented, confirming the mentioned advantages. GLMS turned out to be most suitable for prediction of a random signal with large Gaussian noise.
We develop a novel multistage semiblind multiuser detection technique for the reverse link in direct sequence (DS) code-division multiple access (CDMA) systems. This approach fully utilizes all known users' inform...
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We develop a novel multistage semiblind multiuser detection technique for the reverse link in direct sequence (DS) code-division multiple access (CDMA) systems. This approach fully utilizes all known users' information, performs interference cancellation (IC) to suppress the interferers within the cell, and exploits a blind adaptive decision-directed (DD) MMSE detector to suppress the inter-cell interference. This process can be made iterative and in the multistage process, the tentative decision bits from DD-MMSE detectors can be fed back to the IC part to make interference regeneration more accurate. A simplified adaptive algorithm for this multistage semi-blind detectors is designed. Two upper bounds for the signal-to-noise-interference ratio (SIR) of the multistage semiblind detector are derived. It is shown that the proposed detector has a significant performance gain over that of the pure blind detectors and the non-blind detectors. The tracking capability of the proposed semi-blind detector in a dynamic environment is examined with simulations.
In this paper, we propose two contributions to the simulation and design of an All-Digital Phase-Locked Loop (ADPLL) for RF applications. First, we extend the behavioral model we already proposed, in order to include ...
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In this paper, we propose two contributions to the simulation and design of an All-Digital Phase-Locked Loop (ADPLL) for RF applications. First, we extend the behavioral model we already proposed, in order to include detailed fractional aspects. Second, we propose a new adaptive algorithm that can be integrated in this ADPLL in order to lower its hardware complexity, and argue on a recently proposed algorithm for DCO gain estimation. These points are illustrated through simulations.
Any quadrature IF front-end inherently suffers from mismatch between its I and Q paths. This results in an image rejection degradation, thus decreasing the dynamic range. In this paper, a novel mismatch compensation s...
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Any quadrature IF front-end inherently suffers from mismatch between its I and Q paths. This results in an image rejection degradation, thus decreasing the dynamic range. In this paper, a novel mismatch compensation scheme for a low-IF receiver, but also suitable to many other quadrature front-ends, is proposed. With this approach, gain and phase imbalance corrections result independently from simply two gain adjustments. This allows an analog realization, therefore avoiding costly DSP implementation. In order to compute the wanted compensation gains, an LMS-type adaptive algorithm is also proposed. Its robustness and stability are investigated by extensive simulations.
This paper proposes a new data-selective affine projection algorithm for echo cancellation. The algorithm generalizes the concepts of the conventional set-membership affine-projection by incorporating a lower bound on...
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This paper proposes a new data-selective affine projection algorithm for echo cancellation. The algorithm generalizes the concepts of the conventional set-membership affine-projection by incorporating a lower bound on the output error in order to prevent undesirable attenuation of the far-end signal. It is shown that the echo signal can more reliably be removed from the far-end user signals by employing the new algorithm in double talk situations. In addition, the proposed algorithm retains the fast convergence of the conventional SM-AP algorithm while keeping a reduced number of coefficient updates. Simulation results, using the ITU-T G.168 recommendation setup parameters, are presented in order to confirm the good features of the proposed algorithm
The classification of multi-channel SAR data can be divided into several sequential steps, each of which can be performed by different methods working on different parameter sets. In this work a technique is presented...
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The classification of multi-channel SAR data can be divided into several sequential steps, each of which can be performed by different methods working on different parameter sets. In this work a technique is presented in order to optimize the selection of significant data and the following filtering, parameter extraction and classification operations on the data.
Earlier research has shown that adaptive routing can help in improving network performance. However, it has not received adequate attention in commercial routers mainly due to the additional hardware complexity, and t...
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Earlier research has shown that adaptive routing can help in improving network performance. However, it has not received adequate attention in commercial routers mainly due to the additional hardware complexity, and the perceived cost and performance degradation that may result from this complexity. These concerns can be mitigated if one can design a cost-effective router that can support adaptive routing. This paper proposes a three step recipe-Look-Ahead routing, intelligent Path Selection, and an Economic Storage implementation, called the LAPSES approach-for cost-effective high performance pipelined adaptive router design. The first step, look-ahead routing, reduces a pipeline stage in the router by making table lookup and arbitration concurrent. Next, three new traffic-sensitive path selection heuristics (LRU, LFU and MAX-CREDIT) are proposed to select one of the available alternate paths. Finally, two techniques for reducing routing table size of the adaptive router are presented. These are called meta-table routing and economical storage. The proposed economical storage needs a routing table with only 9 and 27 entries for two and three dimensional meshes, respectively. All these design ideas are evaluated on a (16/spl times/16) mesh network via simulation. A fully adaptive algorithm and various traffic patterns are used to examine the performance benefits. Performance results show that the look-ahead design as well as the path selection heuristics boost network performance, while the economical storage approach turns out to be an ideal choice in comparison to full-table and meta-table options. We believe the router resulting from these three design enhancements can make adaptive routing a viable choice for interconnects.
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