A set of quantum states for colors and another set of quantum states for coordinates are proposed in this paper to represent colors and coordinates of the pixels in an image respectively. We design an algorithm by whi...
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A set of quantum states for colors and another set of quantum states for coordinates are proposed in this paper to represent colors and coordinates of the pixels in an image respectively. We design an algorithm by which an image of pixels and different colors is stored in a quantum system just using qubits. An algorithm for quantum image compression is proposed. Simulation result on the Lena image shows that compression ratio of lossless is 2.058. Moreover, an image segmentation algorithm based on quantumsearchquantumsearch which can find all solutions in the expected times in is proposed, where is the number of pixels and is the number of targets to be segmented.
This paper presents a quantumsearch algorithm for Automated Test Pattern Generation (ATPG) of VLSI circuits. For given digital circuits, a neural network is created that represents the digital gates with their interc...
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This paper presents a quantumsearch algorithm for Automated Test Pattern Generation (ATPG) of VLSI circuits. For given digital circuits, a neural network is created that represents the digital gates with their interconnections as neurons. This neural network is characterized by an energy function E, which is the mathematics representation of neural network. The solution of the energy function gives us the test vector. The test vector is a combination of input values of digital circuits that detects a particular fault. In this paper, specific aspects of quantum theory like superposition and quantum parallelism are applied to find the solution of this energy function. The algorithm developed is so efficient that it requires only root N (where N is the total number of vectors) iterations to find the desired test vector whereas in classical computing, it takes N/2 iterations. At the end, a comparison is made between exhaustive, simulated annealing and quantum based techniques. Experimental results show that the quantum search algorithms are more efficient than classical algorithms and can be applied with more efficiency.
This paper introduces a quantumsearch technique for Automated Test Pattern Generation (ATPG) to test the VLSI circuits. The VLSI testing is viewed as an optimization problem due to its complexity. The digital circuit...
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ISBN:
(纸本)1932415106
This paper introduces a quantumsearch technique for Automated Test Pattern Generation (ATPG) to test the VLSI circuits. The VLSI testing is viewed as an optimization problem due to its complexity. The digital circuits are modeled as a neural network and the problem becomes to minimize the energy function of this neural network. The solution of the equation gives us the test vector. In this paper specific aspects of quantum theory like superposition and quantum parallelism are applied to this problem. The algorithm is so efficient that it requires only VS (where N is the total number of vectors) searches to find the desired test vector, as opposed to a search in classical computing, which on average needs N/2 searches. A comparison is made between exhaustive, simulated annealing and quantum based search techniques. Experimental results show that the quantum search algorithms are more efficient than classical algorithms and can be applied with more efficiency on quantum computers.
This paper presents a quantumsearch algorithm for Automated Test Pattern Generation (ATPG) of combinatorial VLSI circuits. This problem can be viewed as an optimization problem because digital circuits can be modeled...
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ISBN:
(纸本)0780378407
This paper presents a quantumsearch algorithm for Automated Test Pattern Generation (ATPG) of combinatorial VLSI circuits. This problem can be viewed as an optimization problem because digital circuits can be modeled as a neural network. and the problem become to minimize the energy function of this neural network. The solution of the equation gives us the test vector. In this paper specific aspects of quantum theory like superposition and quantum parallelism are applied to this problem. In quantumsearch algorithm this is viewed as a searching problem where the search function (also called oracle) f (x)=1 if the value of the energy function of the neural network is 0 otherwise f (x)=0. quantum mechanics help us to search a group of items simultaneously from the search space rather than one item at a time. The algorithm so efficient that it requires only, on average, roughly rootN (where N is the total number of vectors) searches to find the desired test vector, as opposed to a search in classical computing, which on average needs N/2 searches. A comparison is made between exhaustive, simulated annealing and quantum based search techniques. Experimental results show that the quantum search algorithms are more efficient than classical algorithms and can be applied with more efficiency on a quantum computer.
This paper presents a quantumsearch algorithm for Automated Test Pattern Generation（ATPG） of combinatorial VLSI *** problem can be viewed as an optimization problem because digital circuits can be modeled as a neur...
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ISBN:
(纸本)0780378407
This paper presents a quantumsearch algorithm for Automated Test Pattern Generation（ATPG） of combinatorial VLSI *** problem can be viewed as an optimization problem because digital circuits can be modeled as a neural network and the problem become to minimize the energy function of this neural *** solution of the equation gives us the test *** this paper specific aspects of quantum theory like superposition and quantum parallelism are applied to this *** quantumsearch algorithm this problem is viewed as a searching problem where the search function （also called oracle） f（x）=l if the value of the energy function of the neural network is 0 otherwise f（x）=0. quantum mechanics help us to search a group of items simultaneously from the search space rather than one item at a *** *** efficient that it requires only, on average,roughly N（where N is the total number of vectors） searches to find the desired test vector,as opposed to a search in classical computing,which on average needs N/2 searches.A comparison is made between exhaustive,simulated annealing and quantum based search *** results show that the quantum search algorithms are more efficient than classical algorithms and can be applied with more efficiency on a quantum computer.
I review and expand the model of quantum associative memory that I have recently proposed. In this model binary patterns of n bits are stored in the quantum superposition of the appropriate subset of the computational...
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I review and expand the model of quantum associative memory that I have recently proposed. In this model binary patterns of n bits are stored in the quantum superposition of the appropriate subset of the computational basis of n qbits. Information can be retrieved by performing an input-dependent rotation of the memory quantum state within this subset and measuring the resulting state. The amplitudes of this rotated memory state are peaked on those stored patterns which are closest in Hamming distance to the input, resulting in a high probability of measuring a memory pattern very similar to it. The accuracy of pattern recall can be tuned by adjusting a parameter playing the role of an effective temperature. This model solves the well-known capacity shortage problem of classical associative memories, providing a large improvement in capacity.
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