This paper presents a study of applicability on using smart array systems on a generic multiuser OFDMA system. In this research, three well-known adaptive algorithms such as LMS, SMI and RLS are employed in Pre-FFT sc...
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ISBN:
(纸本)9788476534724
This paper presents a study of applicability on using smart array systems on a generic multiuser OFDMA system. In this research, three well-known adaptive algorithms such as LMS, SMI and RLS are employed in Pre-FFT scheme, and their performances are evaluated in terms of speed of convergence, beamforming and null steering capabilities, and analysis of BER over a multipath fading channel. Good results on multiuser recovering by using spectral and spatial multiplexing demonstrate the reliability on combining OFDMA and adaptive arrays as a way to enhance the system capacity.
The primary objective of this research is to develop adaptive online algorithms for solving the Canadian Traveler Problem (CTP), which is a well-studied problem in the literature that has important applications in dis...
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The primary objective of this research is to develop adaptive online algorithms for solving the Canadian Traveler Problem (CTP), which is a well-studied problem in the literature that has important applications in disaster scenarios. To this end, we propose two novel approaches, namely Maximum Likely Node (MLN) and Maximum Likely Path (MLP), to address the single-agent single-destination variant of the CTP. Our computational experiments demonstrate that the MLN and MLP algorithms together achieve new best-known solutions for 10,715 instances. In the context of disaster scenarios, the CTP can be extended to the multiple-agent multiple-destination variant, which we refer to as MAD-CTP. We propose two approaches, namely MAD-OMT and MAD-HOP, to solve this variant. We evaluate the performance of these algorithms on Delaunay and Euclidean graphs of varying sizes, ranging from 20 nodes with 49 edges to 500 nodes with 1500 edges. Our results demonstrate that MAD-HOP outperforms MAD-OMT by a considerable margin, achieving a replan time of under 9 seconds for all instances. Furthermore, we extend the existing state-of-the-art algorithm, UCT, which was previously shown by Eyerich et al. (2010) to be effective for solving the single-source single-destination variant of the CTP, to address the MAD-CTP problem. We compare the performance of UCT and MAD-HOP on a range of instances, and our results indicate that MAD-HOP offers better performance than UCT on most instances. In addition, UCT exhibited a very high replan time of around 10 minutes. The inferior results of UCT may be attributed to the number of rollouts used in the experiments but increasing the number of rollouts did not conclusively demonstrate whether UCT could outperform MAD-HOP. This may be due to the benefits obtained from using multiple agents, as MAD-HOP appears to benefit to a greater extent than UCT when information is shared among agents.
This work presents generalized low-rank signal decompositions with the aid of switching techniques and adaptive algorithms, which do not require eigen-decompositions, for space-time adaptive processing. A generalized ...
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ISBN:
(纸本)9781457705397
This work presents generalized low-rank signal decompositions with the aid of switching techniques and adaptive algorithms, which do not require eigen-decompositions, for space-time adaptive processing. A generalized scheme is proposed to compute low-rank signal decompositions by imposing suitable constraints on the filtering and by performing iterations between the computed subspace and the low-rank filter. An alternating optimization strategy based on recursive least squares algorithms is presented along with switching and iterations to cost-effectively compute the bases of the decomposition and the low-rank filter. An application to space-time interference suppression in DS-CDMA systems is considered. Simulations show that the proposed scheme and algorithms obtain significant gains in performance over previously reported low-rank schemes.
The simulation approach for assessment of adaptive algorithms based on stochastic search is described in this paper. In this research, the adaptive algorithms are used for railway safety system to improve existing bra...
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ISBN:
(纸本)9781479999781
The simulation approach for assessment of adaptive algorithms based on stochastic search is described in this paper. In this research, the adaptive algorithms are used for railway safety system to improve existing braking by automatic smooth and precise braking of a train, avoiding passing the restrictive signal and prevent crashes. Simulation results are grouped for different types of trains to test the ability and efficiency of adaptive algorithms to find the solution in a wide range of conditions and situations.
The purpose of this research was to compare different adaptive algorithms in terms of their ability to determine temporal gait parameters based on data acquired from inertial measurement units (IMUs). Eight subjects p...
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ISBN:
(纸本)9781457717871
The purpose of this research was to compare different adaptive algorithms in terms of their ability to determine temporal gait parameters based on data acquired from inertial measurement units (IMUs). Eight subjects performed 25 walking trials over a force plate under five different conditions;normal, fast, slow, simulated stiff ankle and simulated stiff knee walking. Data from IMUs worn on the shanks and on the feet were used to identify temporal gait features using three different adaptive algorithms (Green, Selles & Sabatini). Each method's ability to estimate temporal events was compared to the gold standard force plate method for stance time (Greene, r = .990, Selles, r = 0.865, Sabatini, r = 0.980) and double support time (Greene, r = .837, Selles, r = .583, Sabatini, r = .745). The Greene method of estimating gait events from inertial sensor data resulted in the most accurate stance and double support times.
We study reward maximisation in a wide class of structured stochastic multi-armed bandit problems, where the mean rewards of arms satisfy some given structural constraints, e.g. linear, unimodal, sparse, etc. Our aim ...
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ISBN:
(纸本)9781713821120
We study reward maximisation in a wide class of structured stochastic multi-armed bandit problems, where the mean rewards of arms satisfy some given structural constraints, e.g. linear, unimodal, sparse, etc. Our aim is to develop methods that are flexible (in that they easily adapt to different structures), powerful (in that they perform well empirically and/or provably match instance-dependent lower bounds) and efficient in that the per-round computational burden is small. We develop asymptotically optimal algorithms from instance-dependent lower-bounds using iterative saddle-point solvers. Our approach generalises recent iterative methods for pure exploration to reward maximisation, where a major challenge arises from the estimation of the sub-optimality gaps and their reciprocals. Still we manage to achieve all the above desiderata. Notably, our technique avoids the computational cost of the full-blown saddle point oracle employed by previous work, while at the same time enabling finite-time regret bounds. Our experiments reveal that our method successfully leverages the structural assumptions, while its regret is at worst comparable to that of vanilla UCB.
adaptive algorithms offer a wide area of research in the field of digital signal processing. If the received signal is changing with time so as the noise the need for predictive algorithms to be adaptive with the chan...
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ISBN:
(纸本)9781538642542
adaptive algorithms offer a wide area of research in the field of digital signal processing. If the received signal is changing with time so as the noise the need for predictive algorithms to be adaptive with the changes becomes predominant further noise being a random signal strongly needs an adaptive approach for analysis and thus presents a wide scope for research. This paper presents a basic comparative study of various adaptive algorithms such as least mean square (LMS) algorithm, recursive least square (RLS) algorithm and other adaptive algorithms with their application in active noise cancellation. The purpose of presenting this paper is to provide an insight of the initial building blocks of an adaptive algorithm for use in development of further complex algorithms.
This paper derives an expression for the optimal error nonlinearity in adaptive filter design. Using an energy conservation relation, and some typical assumptions, the choice of the error function is optimized by mini...
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ISBN:
(纸本)0780362934
This paper derives an expression for the optimal error nonlinearity in adaptive filter design. Using an energy conservation relation, and some typical assumptions, the choice of the error function is optimized by minimizing the mean-square deviation subject to a fixed rate of convergence. The resulting optimal choice is shown to subsume earlier results as special cases.
This paper presents a cost-effective adaptive feedback Active Noise Control (FANC) method for controlling functional Magnetic Resonance Imaging (fMRI) acoustic noise by decomposing it into dominant periodic components...
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ISBN:
(纸本)9781424479290
This paper presents a cost-effective adaptive feedback Active Noise Control (FANC) method for controlling functional Magnetic Resonance Imaging (fMRI) acoustic noise by decomposing it into dominant periodic components and residual random components. Periodicity of fMRI acoustic noise is exploited by using linear prediction (LP) filtering to achieve signal decomposition. A hybrid combination of adaptive filters-Recursive Least Squares (RLS) and Normalized Least Mean Squares (NLMS) are then used to effectively control each component separately. Performance of the proposed FANC system is analyzed and Noise attenuation levels (NAL) up to 32.27dB obtained by simulation are presented which confirm the effectiveness of the proposed FANC method.
This paper presents a rigous conditions, without the independence assumtion on the input signal, for the first and second moment convergence of the gradient adaptive algorithms including FIR and IIR (equation error me...
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