By the study of the pattern book Ying Zao Fa Shi (building regulations of Song Dynasty, 1103 AD), while analyzing the combining and dimensioning rule of timber framework and tile work, a model self-generating program ...
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By the study of the pattern book Ying Zao Fa Shi (building regulations of Song Dynasty, 1103 AD), while analyzing the combining and dimensioning rule of timber framework and tile work, a model self-generating program has been compiled for the first time. The operating framework has been firstly defined, while solving the issues of clustering principle, connecting method, output classification, etc. with the detailed description of algorithm theory. Taking the corner bracket set and nine-ridge roof for example, after the compilation and debug by Grasshopper, according to various input parameters, various models have been generated automatically by the plugin, proving the velocity and the veracity of the algorithm.
In this study, we visualise the search trajectories of a genetic programming system as graph-based models, where nodes are genotypes/phenotypes and edges represent their mutational transitions. We also quantitatively ...
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ISBN:
(纸本)9783031295720;9783031295737
In this study, we visualise the search trajectories of a genetic programming system as graph-based models, where nodes are genotypes/phenotypes and edges represent their mutational transitions. We also quantitatively measure the characteristics of phenotypes including their genotypic abundance (the requirement for neutrality) and Kolmogorov complexity. We connect these quantified metrics with search trajectory visualisations, and find that more complex phenotypes are under-represented by fewer genotypes and are harder for evolution to discover. Less complex phenotypes, on the other hand, are over-represented by genotypes, are easier to find, and frequently serve as stepping-stones for evolution.
Empirical Mode Decomposition (EMD) is widely used in biomedical field especially for electrocardiogram (ECG) signal processing. The combination of EMD with Hilbert Transform, the Hilbert Huang Transform (HHT), offers ...
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ISBN:
(纸本)9781424471706
Empirical Mode Decomposition (EMD) is widely used in biomedical field especially for electrocardiogram (ECG) signal processing. The combination of EMD with Hilbert Transform, the Hilbert Huang Transform (HHT), offers higher frequency resolution and more accurate timing of transient non-stationary signals than conventional integral transform techniques. Embedded computing and signal processing chips with sufficient performance are involved in the application of HHT in data streams. The original HHT algorithm, especially in the case of EMD, is not suitable in such systems so an incremental algorithm is necessary for efficient computation. In this paper an investigation of the EMD performance is presented in terms of computation time that is necessary for smart resource management. A metric is proposed aiming at the a priori calculation of computation time based on ECG time series characteristics.
This paper discusses the constrained stochastic gradient (CSG) algorithm used for controlling antenna arrays, aiming to maximize the signal-to-interference-plus-noise ratio (SINR) in mobile communications. Firstly, an...
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This paper discusses the constrained stochastic gradient (CSG) algorithm used for controlling antenna arrays, aiming to maximize the signal-to-interference-plus-noise ratio (SINR) in mobile communications. Firstly, analytical expressions for the first moment of the weight vector and the SINR characteristic of the standard CSG algorithm are derived for two interferer signals, considering small step-size conditions and assuming Gaussian signal, interference, and noise. From these model expressions, the CSG algorithm performance is assessed, which predicts undesired behavior (termed here unbalanced behavior, pertaining to an unbalance between maximizing signal power and minimizing interference power) when one or more interference angles-of-arrival are close to the signal angle-of-arrival and the angle-of-arrival spreads of the involved signals are small. Finally, by using the model expressions, an improved CSG (ICSG) algorithm is proposed to compensate the unbalanced behavior of the standard CSG algorithm. The accuracy of the proposed model and the effectiveness of the modified algorithm are assessed through numerical simulations.
The definition of a generic algorithm model for representing arbitrary heuristic optimization algorithms is one of the most challenging tasks when developing heuristic optimization software systems. As a high degree o...
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ISBN:
(纸本)9788890372407
The definition of a generic algorithm model for representing arbitrary heuristic optimization algorithms is one of the most challenging tasks when developing heuristic optimization software systems. As a high degree of flexibility and a large amount of reusable code are requirements that are hard to fulfill together, existing frameworks often lack of either of them to a certain extent. To overcome these difficulties the authors present a generic algorithm model not only capable of representing heuristic optimization but that can be used for modeling arbitrary algorithms. This model can be used as a meta-model for heuristic optimization algorithms, enabling users to represent custom algorithms in a flexible way by still providing a broad spectrum of reusable algorithm building blocks.
Designing efficient parallel algorithms in a message-based parallel computer should consider both time-space tradeoffs and computation-communication tradeoffs. In order to balance these tradeoffs and achieve the optim...
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Designing efficient parallel algorithms in a message-based parallel computer should consider both time-space tradeoffs and computation-communication tradeoffs. In order to balance these tradeoffs and achieve the optimal performance of an algorith, one has to consider various design parameters such as the number of processors required and the size of partitions. In this paper, we demonstrate that, for certain data parallel algorithms, it is possible to determine these design parameters analytically. To serve as a basis for the discussions that follow, a simple model for the NCUBE hypercube computer is introduced. Using this model, we use two examples, array summation and matrix multiplication, to illustrate how their performance can be modeled. By optimizing these expressions, one is able to determine optimal design parameters which arrive at efficient execution. Experiments on a 64-node NCUBE verified the accuracy of the analytic results and are used to further support the discussions.
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