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.
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.
We introduce an online adaptive algorithm for learning gesture models. By learning gesture models in an online fashion, the gesture recognition process is made more robust, and the need to train on a large training en...
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ISBN:
(纸本)0769507506
We introduce an online adaptive algorithm for learning gesture models. By learning gesture models in an online fashion, the gesture recognition process is made more robust, and the need to train on a large training ensemble is obviated. Hidden Markov models are used to represent the spatial and temporal structure of the gesture. The usual output probability distributions-typically representing appearance-are trained at runtime exploiting the temporal structure (Markov model) that is either trained off-line or is explicitly hand-coded. In the early stages of runtime adaptation, contextural information derived from the application is used to bias the expectation as to which Markov state the system is in at any given time. We describe the Watch and Learn system, a computer vision system which is able to learn simple gestures online for interactive control.
An algorithm using wavelets and Kalman filtering method has been developed for QRS detection. The algorithm takes following steps: i) We use a RLS adaptive algorithm to establish a model of the electrocardiogram. Thus...
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An algorithm using wavelets and Kalman filtering method has been developed for QRS detection. The algorithm takes following steps: i) We use a RLS adaptive algorithm to establish a model of the electrocardiogram. Thus the algorithm can change its own model according to the change of the electrocardiogram, ii) Based on the model established in stage i), we combined the wavelet and Kalman algorithm, decomposed the signal to several scales, filtering the signal in each scale. And then, iii) A decision rule is used to determine the QRS complex. The method was tested on ECG data form the MIT database, and experimental results show that the method is effective, and the influence of the noise can be eliminated
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.
In wireless networks where all users have different channel characteristics and service classes, it is challenging to design an adaptive scheduler to support quality of service (QoS). Some fraction of multiuser divers...
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In wireless networks where all users have different channel characteristics and service classes, it is challenging to design an adaptive scheduler to support quality of service (QoS). Some fraction of multiuser diversity gain, which offers significant capacity increase, should be sacrificed to meet certain QoS targets. We present an opportunistic scheduling scheme under resource-sharing constraints. The scheduler solves the weighted fairness by diverting a fraction of resources from surplus users to underserved users. Given the average received signal-to-noise ratios (SNR) of users and resource-sharing constraints, the capacity of the proposed scheduler is analyzed over Rayleigh fading channels. Degree of weighted fairness for various scheduling schemes is also provided. Numerical results illustrate that while sacrificing a fraction of the achievable total capacity the proposed scheduler provides perfect weighted fairness.
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.
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.
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.
adaptive channel equalization algorithms are commonly used in wireless communications receivers to counter intersymbol interference, multipath dispersion, and other time varying channel degradations. We obtain approxi...
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adaptive channel equalization algorithms are commonly used in wireless communications receivers to counter intersymbol interference, multipath dispersion, and other time varying channel degradations. We obtain approximate expressions for the increase in mean square error of the LMS adaptive algorithm when the total processing power is decreased by reducing the number of data and filter coefficient bits used by the algorithm. We also obtain expressions for the power-optimal bit-allocation factor which determines the proportion of the bits allocated to the data vs. allocated to the coefficients. Numerical studies are presented for an exponential memory ISI channel and 4-ary PSK signalling. These studies indicate that as few as 8 bits total are needed to equalize the channel and that most of these bits (6 out of 8) should be allocated to the filter coefficients.
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