In this paper, we present channel equalization technique for orthogonal frequency division multiplexing (OFDM) systems in noisy channel using rls. The proposed technique has a good performance in noisy channel. It imp...
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In this paper, we present channel equalization technique for orthogonal frequency division multiplexing (OFDM) systems in noisy channel using rls. The proposed technique has a good performance in noisy channel. It improves the communication quality. We have compared the performances of the presented technique by measuring bit error rate with 16-QAM, 32-QAM and 64-QAM as modulation schemes.
Combinations of adaptive filters have attracted attention as a simple solution to improve filter performance, including tracking properties. In this paper, we consider combinations of LMS and rls filters, and study th...
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ISBN:
(纸本)9781424442959
Combinations of adaptive filters have attracted attention as a simple solution to improve filter performance, including tracking properties. In this paper, we consider combinations of LMS and rls filters, and study their performance for tracking time-varying solutions. We show that a combination of two filters from the same family (i.e., two LMS or two rls filters) cannot improve the performance over that of a single filter of the same type with optimal selection of the step size (or forgetting factor). However, combining LMS and rls filters it is possible to simultaneously outperform the optimum LMS and rls filters. In other words, combination schemes can achieve smaller errors than optimally adjusted individual filters. Experimental work in a plant identification setup corroborates the validity of our results.
The method for camera motion estimation is proposed for the moving objects. Whereas the estimation of the structure and motion (SaM) of the moving objects usually involves the constraints on the motion of the camera a...
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ISBN:
(纸本)9781467317139
The method for camera motion estimation is proposed for the moving objects. Whereas the estimation of the structure and motion (SaM) of the moving objects usually involves the constraints on the motion of the camera and the object, the moving camera velocities can be estimated in our work using the images of the moving object from the single camera without any constraint on the camera and object motion. To this end, the dynamics of the partially measurable state are arranged in such a way that the recursive least-squares (rls) algorithm can be employed for stationary objects and then the nonlinear observer based on RISE (robust integral signed error) method for dynamic objects sequentially. The proposed method has advantages in that when the proposed method and the previously developed SaM algorithms are combined together, we can reconstruct the 3-D structure of the moving objects from 2-D images from a single camera. Simulation results under time-varying velocities of both camera and object are presented to verify the proposed method.
In electric and hybrid vehicles,driving performance is strongly influenced by the battery aging *** most lithium-ion batteries,thepower capability fade caused by battery impedance rise is the main reason for battery *...
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In electric and hybrid vehicles,driving performance is strongly influenced by the battery aging *** most lithium-ion batteries,thepower capability fade caused by battery impedance rise is the main reason for battery *** this paper,an online diagnosingmethod of intemalresistance is presented based on equivalent circuit impedance *** a special diagnosing signal,voltage response is recorded and the impedance model is parameterized with the help of recursive least square (rls) *** values of impedance model are then used for the estimation of power capability and detection of battery *** performance of the internal resistance monitoring method is proved in Matlab/Simulink,which shows little error in estimation of battery power capability.
This paper examines the performance of an adaptive linear array employing the new RLMS algorithm, which consists of a recursive least square (rls) section followed by a least mean square (LMS) section. The performance...
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This paper examines the performance of an adaptive linear array employing the new RLMS algorithm, which consists of a recursive least square (rls) section followed by a least mean square (LMS) section. The performance measures used are output and input signal-to-interference plus noise ratios (SINR), side lobe level (SLL), and SINRo as a function of the direction of arrival of the interfering signal. Computer simulation results show that the performance of RLMS is superior to either the rls or LMS based on these measures, particularly when operating with low input SINR.
The interaction between memory and nonlinear factors of Wiener Power Amplifier(WPA)leads to slower convergence speed and limited convergence precision when applying conventional predistortion *** on the Hammerstein Pr...
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The interaction between memory and nonlinear factors of Wiener Power Amplifier(WPA)leads to slower convergence speed and limited convergence precision when applying conventional predistortion *** on the Hammerstein Predistorter(HPD)model,a novel adaptive separated predistor- tion method was proposed in this *** method identifies one of the memory and nonlinear characteristics of HPD on the assumption that HPD has compensated the other characteristic of WPA *** found that with the increasing of the number of iteration,this assumption becomes true,and lastly, the coefficients of HPD converge to the global optimal solutions. The proposed method has several ***,based on indirect learning modeling,there is no need for the proposed method to identify the characteristics of ***,with a post-distorter on the feed-back path to compensate the nonlinearity of WPA,the method improves the precision of the estimation of PD coefficients *** finally,the proposed method uses the adaptive Recursive Least Square(rls)algorithm to get faster convergence *** results confirm that the proposed method exhibits better linearization performance and faster convergence speed compared to the exiting adaptive predistortion method for WPA.
In cognitive radio systems, the accuracy of spectrum sensing depends on the received primary signal strength at the secondary user (SU). In fact, a single node sensing would be compromised if the received signal stren...
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ISBN:
(纸本)9781467318808
In cognitive radio systems, the accuracy of spectrum sensing depends on the received primary signal strength at the secondary user (SU). In fact, a single node sensing would be compromised if the received signal strength is not high enough to be detected by this node. In this paper, we propose a cooperative decision fusion rule based on adaptive linear combiner. The weights which correspond to confidence levels affected to SUs, are determined adaptively using the Normalized Least Mean Squares (NLMS) and the Recursive Mean Squares (rls) algorithms. The proposed algorithms combine the SUs decisions with the adaptive confidence levels to track the surrounding environment. Simulation results show a high adaptability of the proposed scheme, as the operating conditions change. Furthermore, the proposed algorithms do not necessitate a prior knowledge about the PU features and are very efficient compared to conventional decision fusion techniques.
This paper presents and investigates recursive order tracking (OT) techniques based on the least mean-square (LMS) method and the Vold-Kalman (VK) algorithm with a one pole structural equation, both of which could be ...
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This paper presents and investigates recursive order tracking (OT) techniques based on the least mean-square (LMS) method and the Vold-Kalman (VK) algorithm with a one pole structural equation, both of which could be realized as real-time applications. Additionally, for comparisons, two common adaptive OT filters are considered: the recursive least-squares (rls) method and the VK algorithm with a two pole structural equation. The numerical implementations of the considered methods, through simulations on a representative noisy synthetic signal, including both close and crossing orders spectral components, are performed. The results indicate a possible degradation in the tracking performance of the rls algorithm and the effectiveness of the simple LMS method, as well as both considered VK algorithms, for OT and distinguishing. The influence of the sampling frequency on the choosing of a weighting factor for the VK recursive OT filters is further investigated to extend the guidelines from the literature for using these methods. Two examples of practical implementations of the considered recursive OT methods are given: (i) the separation of the crossing orders arising in the laboratory test bench of the two unbalanced rotors rotating at independent frequencies and (ii) the one engineering application of fault diagnosis in the massive reduction gear on an excavator with a cable crowd, based on the distinguishing and separation of close orders. The experimental results justify the implementation of the proposed techniques as OT tools in industrial applications.
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