This study presents a field programmable gate array (FPGA) implementation of a simple fault-tolerant control that ensures continuous operation of hysteresis current controlled AC machine drives under faulty current se...
详细信息
This study presents a field programmable gate array (FPGA) implementation of a simple fault-tolerant control that ensures continuous operation of hysteresis current controlled AC machine drives under faulty current sensor. The adopted control requires the use of three current sensors and is available for three-phase isolated neutral systems. The third current sensor allows the faulty current sensor detection and isolation based on analytical redundancy that provides residuals with well-defined thresholds. The control is reconfigured in case of faulty current measurement and operation continuity is performed using the remaining two healthy sensors. The main interest of using FPGAs to implement such controllers is the very important reduction of execution time delay in spite of algorithm complexity. As a result, a high sampling frequency can be used and the residual thresholds can be accurately defined even for the experimental set-up. Numerous experimental results are given to illustrate the efficiency of FPGA-based solutions to achieve efficient and reliable fault-tolerant hysteresis current control of AC machine drives.
Active noise control (ANC) is a methodology for attenuating noise based on adaptive signal processing algorithms. ANC is well assessed for the attenuation of Gaussian noise, but the rejection of non-Gaussian impulsive...
详细信息
Active noise control (ANC) is a methodology for attenuating noise based on adaptive signal processing algorithms. ANC is well assessed for the attenuation of Gaussian noise, but the rejection of non-Gaussian impulsive noise signals represents a much more critical task that may even impair algorithm convergence. To overcome this problem the adaptive filter weight update process must be modified by discarding or discounting samples associated with impulsive noise. This can be done either by modeling the impulsive noise with a non-Gaussian distribution such as the Symmetric alpha-stable (S alpha S) distribution or by applying an outlier detection method. With both approaches the accuracy in the noise description appears to be crucial for effective noise reduction. This paper proposes two novel approaches for the attenuation of impulsive noise both for invariant and time-varying noise distributions. The first one is based on the on-line estimation of an S alpha S model of the noise probabilistic description. The second relies on a simple on-line recursive procedure that reliably estimates amplitude thresholds for outlier detection. Both methods compare favorably with competitor approaches, while maintaining a sufficiently low algorithm complexity. Several examples are shown to demonstrate the algorithms' effectiveness. (C) 2011 Elsevier Ltd. All rights reserved.
A fasciagraph consists of a sequence of copies of the same graph, each copy being linked to the next one according to a regular scheme. More precisely, a fasciagraph is characterized by an integer n (the number of cop...
详细信息
A fasciagraph consists of a sequence of copies of the same graph, each copy being linked to the next one according to a regular scheme. More precisely, a fasciagraph is characterized by an integer n (the number of copies or fibers) and a mixed graph M. In a rotagraph, the last copy is also linked to the first one. In the literature, similar methods were used to address various problems on rotagraphs and fasciagraphs. The goal of our work is to define a class of decision problems for which this kind of method works. For this purpose, we introduce the notion of pseudo-d-local q-properties of fasciagraphs and rotagraphs. For a mixed graph M and a pseudo-d-local q-property P, we propose a generic algorithm for rotagraphs (respectively, fasciagraphs) that computes in one run the data that allow one to decide, for any integer n >= d (respectively, n >= d + 2), whether the rotagraph (respectively, fasciagraph) of length n based on M satisfies P, using only a small number of elementary operations independent of n. (C) 2012 Elsevier B.V. All rights reserved.
In this paper, we prove that the derivability problems for product-free Lambek calculus and product-free Lambek calculus allowing empty premises are NP-complete. Also we introduce a new derivability characterization f...
详细信息
In this paper, we prove that the derivability problems for product-free Lambek calculus and product-free Lambek calculus allowing empty premises are NP-complete. Also we introduce a new derivability characterization for these calculi. (c) 2011 Elsevier B.V. All rights reserved.
Synthetic pattern generation procedures have various applications, and a number of approaches (fractals, L-systems, etc.) have been devised. A fundamental underlying question is: will new pattern generation algorithms...
详细信息
Synthetic pattern generation procedures have various applications, and a number of approaches (fractals, L-systems, etc.) have been devised. A fundamental underlying question is: will new pattern generation algorithms continue to be invented, or is there some "universal'' algorithm that can generate all (and only) the perceptually distinguishable images, or even all members of a restricted class of patterns such as logos or letterforms? In fact there are many complete algorithms that can generate all possible images, but most images are random and not perceptually distinguishable. Counting arguments show that the percentage of distinguishable images that will be generated by such complete algorithms is vanishingly small. In this paper we observe that perceptually distinguishable images are compressible. Using this observation it is evident that algorithmic complexity provides an appropriate framework for discussing the question of a universal image generator. We propose a natural thesis for describing perceptually distinguishable images and argue its validity. Based on it, we show that there is no program that generates all (and only) these images. Although this is an abstract result, it may have importance for graphics and other fields that deal with compressible signals. In essence, new representations and pattern generation algorithms will continue to be developed;there is no feasible "super algorithm'' that is capable of all things. (C) 2011 Elsevier Inc. All rights reserved.
As computer systems scale in the number of processors, scalable data structures with good parallel performance become increasingly important. Lock-free data structures promise such improved parallel performance at the...
详细信息
ISBN:
(纸本)9781479910090
As computer systems scale in the number of processors, scalable data structures with good parallel performance become increasingly important. Lock-free data structures promise such improved parallel performance at the expense of higher algorithmic complexity and higher sequential execution time overhead. All lock-free data structures are based on simple atomic operations that, though supported by modern processors, are expensive in execution time. We present a lock-free data structure, ELB-trees, which under certain assumptions can be used as multimaps as well as priority queues. Specifically it cannot store duplicate key-value pairs, and it is not linearizable. Compared to existing data structures, ELB-trees require fewer atomic operations leading to improved performance. We measure the parallel performance of ELB-trees using a set of benchmarks and observe that ELB-trees are up to almost 30 times faster than library multimap implementations.
It is a well-known fact that the Bayesian Networks' (BNs) use as classifiers in different fields of application has recently witnessed a noticeable growth. Yet, the Naive Bayes' application, and even the augme...
详细信息
ISBN:
(纸本)9783642318368
It is a well-known fact that the Bayesian Networks' (BNs) use as classifiers in different fields of application has recently witnessed a noticeable growth. Yet, the Naive Bayes' application, and even the augmented Naive Bayes', to classifier-structure learning, has been vulnerable to certain limits, which explains the practitioners' resort to other more sophisticated types of algorithms. Consequently, the use of such algorithms has paved the way for raising the problem of super-exponential increase in computational complexity of the Bayesian classifier learning structure, with the increasing number of descriptive variables. In this context, the present work's major objective lies in setting up a further solution whereby a remedy can be conceived for the intricate algorithmic complexity imposed during the learning of Bayesian classifiers' structure with the use of sophisticated algorithms. Noteworthy, the present paper's framework is organized as follows. We start, in the first place, by to propose a novel approach designed to reduce the algorithmic complexity without engendering any loss of information when learning the structure of a Bayesian classifier. We, then, go on to test our approach on a car diagnosis and a Lymphography diagnosis databases. Ultimately, an exposition of our conducted work's interests will be a closing step to this work.
We present new analysis, algorithmic techniques, and implementations of the Fast Multipole Method (FMM) for solving N-body problems. Our research specifically addresses two key challenges. The first challenge is how t...
详细信息
ISBN:
(纸本)9780769546766
We present new analysis, algorithmic techniques, and implementations of the Fast Multipole Method (FMM) for solving N-body problems. Our research specifically addresses two key challenges. The first challenge is how to engineer fast code for today's platforms. We present the first in-depth study of multicore optimizations and tuning for FMM, along with a systematic approach for transforming a conventionally-parallelized FMM into a highly-tuned one. We introduce novel optimizations that significantly improve the within-node scalability of the FMM, thereby enabling high-performance in the face of multicore and manycore systems. The second challenge is how to understand scalability on future systems. We present a new algorithmic complexity analysis of the FMM that considers both intra-and inter-node communication costs. This analysis yields the surprising prediction that although the FMM is largely compute-bound today, and therefore highly scalable on current systems, the trajectory of processor architecture designs-if there are no significant changes-could cause it to become communication-bound as early as the year 2020. This prediction suggests the utility of our analysis approach, which directly relates algorithmic and architectural characteristics, for enabling a new kind of high-level algorithm-architecture co-design.
Synthetic pattern generation procedures have various applications, and a number of approaches (fractals, L-systems, etc.) have been devised. A fundamental underlying question is: will new pattern generation algorithms...
详细信息
Synthetic pattern generation procedures have various applications, and a number of approaches (fractals, L-systems, etc.) have been devised. A fundamental underlying question is: will new pattern generation algorithms continue to be invented, or is there some "universal'' algorithm that can generate all (and only) the perceptually distinguishable images, or even all members of a restricted class of patterns such as logos or letterforms? In fact there are many complete algorithms that can generate all possible images, but most images are random and not perceptually distinguishable. Counting arguments show that the percentage of distinguishable images that will be generated by such complete algorithms is vanishingly small. In this paper we observe that perceptually distinguishable images are compressible. Using this observation it is evident that algorithmic complexity provides an appropriate framework for discussing the question of a universal image generator. We propose a natural thesis for describing perceptually distinguishable images and argue its validity. Based on it, we show that there is no program that generates all (and only) these images. Although this is an abstract result, it may have importance for graphics and other fields that deal with compressible signals. In essence, new representations and pattern generation algorithms will continue to be developed;there is no feasible "super algorithm'' that is capable of all things. (C) 2011 Elsevier Inc. All rights reserved.
We investigated the performance, through simulations, of multi-channel digital back-propagation-based nonlinearity compensation (NLC) for digital Nyquist WDM transmission over uncompensated standard SMF links. We also...
详细信息
ISBN:
(纸本)9781467362740
We investigated the performance, through simulations, of multi-channel digital back-propagation-based nonlinearity compensation (NLC) for digital Nyquist WDM transmission over uncompensated standard SMF links. We also review recently developed approaches to reduce NLC algorithm complexity.
暂无评论