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In this paper, we present a gradient algorithm to identify a damping rate function for a non-Markovian single qubit system. The dynamics of the single qubit system in a non-Markovian environment are assumed to obey a time convolutionless master equation, where all the non-Markovian effects of the environment are combined in the unknown damping rate function. To identify the damping rate function,...
Domain adaptation learning (DAL) investigates how to perform a task across different domains. In this paper, we present a kernelized local–global approach to solve domain adaptation problems. The basic idea of the proposed method is to consider the global and local information regarding the domains (e.g., maximum mean discrepancy and intraclass distance) and to convert the domain adaptation problem...
Data compression has been playing an important role in the areas of data transmission. Many great contributions have been made in this area, such as Huffman coding, LZW algorithm, run length coding, and so on. These methods only focus on the data compression. On the other hand, it is very important for us to encrypt our data to against malicious theft and attack during transmission. A novel algorithm...
It is well-known that the traditional association rules with time can't be found out in many algorithms. First, according to concept of dynamic association rules, this paper analyzes the disadvantages of traditional association rules. Then, the concepts of dynamic association rules based on sliding windows and the definition of time vector representation of dynamic association rules are put forward...
In this paper, an improved gene expression-based clonal selection algorithm (IGE-CSA) is proposed, which is aimed at solving synthesis problems of combinational logic circuits. The encoding of gene expression programming (GEP) is improved. Compared with GEP encoding, the proposed encoding is more compact and fits to represent multi-output combinational logic circuit. Clonal selection algorithm (CSA)...
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