This paper presents a data filtering based stochastic gradient algorithm for estimating the parameters of multivariable Hammerstein FIR-MA-like systems. By filtering the input and output data, the FIR-MA-like model is...
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This paper presents a data filtering based stochastic gradient algorithm for estimating the parameters of multivariable Hammerstein FIR-MA-like systems. By filtering the input and output data, the FIR-MA-like model is transformed into a controlled autoregressive model. The examples confirm that the proposed algorithm is more accurate and has a better performance than the stochastic gradient algorithm. (C) 2015 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
Artificial neural network has been extensively consumed training model for solving pattern recognition tasks. However, training a very huge training data set using complex neural network necessitates excessively high ...
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Artificial neural network has been extensively consumed training model for solving pattern recognition tasks. However, training a very huge training data set using complex neural network necessitates excessively high training time. In this correspondence, a new fast Linear Adaptive Skipping Training (LAST) algorithm for training artificial neural network (ANN) is instituted. The core essence of this paper is to ameliorate the training speed of ANN by exhibiting only the input samples that do not categorize perfectly in the previous epoch which dynamically reducing the number of input samples exhibited to the network at every single epoch without affecting the network's accuracy. Thus decreasing the size of the training set can reduce the training time, thereby ameliorating the training speed. This LAST algorithm also determines how many epochs the particular input sample has to skip depending upon the successful classification of that input sample. This LAST algorithm can be incorporated into any supervised training algorithms. Experimental result shows that the training speed attained by LAST algorithm is preferably higher than that of other conventional training algorithms.
The explosive growth of Internet applications and content, during the last decade, has revealed an increasing need for information filtering and recommendation. Most research in the area of recommendation systems has ...
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The explosive growth of Internet applications and content, during the last decade, has revealed an increasing need for information filtering and recommendation. Most research in the area of recommendation systems has focused on designing and implementing efficient algorithms that provide accurate recommendations. However, the selection of appropriate recommendation content and the presentation of information are equally important in creating successful recommender applications. This paper addresses issues related to the presentation of recommendations in the movies domain. The current work reviews previous research approaches and popular recommender systems, and focuses on user persuasion and satisfaction. In our experiments, we compare different presentation methods in terms of recommendations' organization in a list (i.e. top N-items list and structured overview) and recommendation modality (i.e. simple text, combination of text and image, and combination of text and video). The most efficient presentation methods, regarding user persuasion and satisfaction, proved to be the "structured overview" and the "text and video" interfaces, while a strong positive correlation was also found between user satisfaction and persuasion in all experimental conditions.
Among the most promising and active research areas in heuristic optimisation is the field of adaptive memetic algorithms (AMAs). These gain much of their reported robustness by adapting the probability with which each...
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Among the most promising and active research areas in heuristic optimisation is the field of adaptive memetic algorithms (AMAs). These gain much of their reported robustness by adapting the probability with which each of a set of local improvement operators is applied, according to an estimate of their current value to the search process. This paper addresses the issue of how the current value should be estimated. Assuming the estimate occurs over several applications of a meme, we consider whether the extreme or mean improvements should be used, and whether this aggregation should be global, or local to some part of the solution space. To investigate these issues, we use the well-established COMA framework that coevolves the specification of a population of memes (representing different local search algorithms) alongside a population of candidate solutions to the problem at hand. Two very different memetic algorithms are considered: the first using adaptive operator pursuit to adjust the probabilities of applying a fixed set of memes, and a second which applies genetic operators to dynamically adapt and create memes and their functional definitions. For the latter, especially on combinatorial problems, credit assignment mechanisms based on historical records, or on notions of landscape locality, will have limited application, and it is necessary to estimate the value of a meme via some form of sampling. The results on a set of binary encoded combinatorial problems show that both methods are very effective, and that for some problems it is necessary to use thousands of variables in order to tease apart the differences between different reward schemes. However, for both memetic algorithms, a significant pattern emerges that reward based on mean improvement is better than that based on extreme improvement. This contradicts recent findings from adapting the parameters of operators involved in global evolutionary search. The results also show that local reward schemes o
This paper proposes four resource (subcarriers-and-bits) allocation methods for OFDMA-based multiuser MIMO system. We employ adaptive modulation according to the channel state information (CSI) of each user to meet th...
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This paper proposes four resource (subcarriers-and-bits) allocation methods for OFDMA-based multiuser MIMO system. We employ adaptive modulation according to the channel state information (CSI) of each user to meet the symbol error rate (SER) requirement. The first scheme is based on transmit spatial diversity (TSD), in which the vector channel with the highest gain between the base station and specific antenna at remote terminal is chosen for transmission. The second scheme assigns subcarrier to the best user and employs spatial multiplexing on the MIMO system to further enhance the throughput. The space-division multiple-access (SDMA) scheme assigns single subcarrier simultaneously to the remote terminals with pairwise "nearly orthogonal" spatial signatures. In the fourth scheme, we propose to design the transmit beamformers based on the zero-forcing (ZF) criterion such that the multi-user interference (MTH) is completely removed. Moreover, spatial multiplexing technique is jointly exploited to achieve throughput multiplication. Numerical results demonstrate that all the proposed algorithms are simple and reliable and the fourth scheme is the best since all users are allowed to share single subcarrier. (C) 2017 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
Admissible multicast traffic can be efficiently handled in high-capacity Internet routers using packet circulation. Presented is a practical algorithm for the building and maintenance of the circulation tree, as well ...
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Admissible multicast traffic can be efficiently handled in high-capacity Internet routers using packet circulation. Presented is a practical algorithm for the building and maintenance of the circulation tree, as well as a report on its implementation. Its scalability and speed were assessed, and shown to be satisfactory.
The article presents the results of a study which investigated the effectiveness of Google's translation service for searching the internet using multiple languages. It was found that asking Google to automaticall...
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The article presents the results of a study which investigated the effectiveness of Google's translation service for searching the internet using multiple languages. It was found that asking Google to automatically translate search terms reduces search effectiveness. These performance reductions were generally due to the characteristic problems associated with mechanical translation, and varied between language pairs. Using one intermediary language, into which all search terms were translated, and from which all subsequent translations were made, was found to improve the results.
Wafer fabs are under constant pressure to deliver semiconductor products as quickly as possible to an eagerly awaiting consumer market. As a result, mask suppliers are often required to reduce their delivery time for ...
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Wafer fabs are under constant pressure to deliver semiconductor products as quickly as possible to an eagerly awaiting consumer market. As a result, mask suppliers are often required to reduce their delivery time for high-end reticles used in the fabrication of silicon wafers. By reducing the optical inspection time (a critical step needed to ensure no defects are present within the designed mask patterns), precious manufacturing time can be saved. This time savings is especially important for tritone reticles that require extra manufacturing and inspection steps over traditional binary masks. By using a recently developed reticle inspection system, database optical inspection of tritone reticles can be achieved in nearly half the time previously needed.
Evolvable hardware (EHW) refers to one particular type of hardware whose architecture, structure and functions change dynamically and autonomously in order to improve its performance in performing certain tasks. The e...
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Evolvable hardware (EHW) refers to one particular type of hardware whose architecture, structure and functions change dynamically and autonomously in order to improve its performance in performing certain tasks. The emergence of this new field has been influenced profoundly by the progress in reconfigurable hardware and evolutionary computation. Traditional hardware is notorious for its inflexibility. It is impossible to change the hardware's structure and functions once it is made. However, most real-world problems are not fixed. They change with time. In order to deal with these problems efficiently and effectively, different hardware structures are necessary. EHW provides an ideal approach making hardware 'soft' by adapting the hardware structure to a problem dynamically. There have been some concerns in recent years over the black-box nature of EHW, since it is often very difficult to analyze and understand circuits evolved by evolutionary algorithms. These concerns are natural and appear in other bio-.inspired systems as well, such as in artificial neural networks.
Models are core artefacts in software development and maintenance. Consequently, quality of models, especially maintainability and extensibility, becomes a big concern for most non-trivial applications. For some reaso...
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Models are core artefacts in software development and maintenance. Consequently, quality of models, especially maintainability and extensibility, becomes a big concern for most non-trivial applications. For some reasons, software models usually contain some duplications. These duplications had better be detected and removed because the duplications may reduce maintainability, extensibility and reusability of models. As an initial attempt to address the issue, the author propose an approach in this study to detecting duplications in sequence diagrams. With special preprocessing, the author convert 2-dimensional (2-D) sequence diagrams into an 1-D array. Then the author construct a suffix tree for the array. With the suffix tree, duplications are detected and reported. To ensure that every duplication detected with the suffix tree can be extracted as a separate reusable sequence diagram, the author revise the traditional construction algorithm of suffix trees by proposing a special algorithm to detect the longest common prefixes of suffixes. The author also probe approaches to removing duplications. The proposed approach has been implemented in DuplicationDetector. With the implementation, the author evaluated the proposed approach on six industrial applications. Evaluation results suggest that the approach is effective in detecting duplications in sequence diagrams. The main contribution of the study is an approach to detecting duplications in sequence diagrams, a prototype implementation and an initial evaluation.
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