A quantum BP neural networks model with learning algorithm is proposed. First, based on the universality of single qubit rotation gate and two-qubit controlled-NOT gate, a quantum neuron model is constructed, which is...
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A quantum BP neural networks model with learning algorithm is proposed. First, based on the universality of single qubit rotation gate and two-qubit controlled-NOT gate, a quantum neuron model is constructed, which is composed of input, phase rotation, aggregation, reversal rotation and output. In this model, the input is described by qubits, and the output is given by the probability of the state in which (1) is observed. The phase rotation and the reversal rotation are performed by the universal quantum gates. Secondly, the quantum BP neural networks model is constructed, in which the output layer and the hide layer are quantum neurons. With the application of the gradient descent algorithm, a learning algorithm of the model is proposed, and the continuity of the model is proved. It is shown that this model and algorithm are superior to the conventional BP networks in three aspects: convergence speed, convergence rate and robustness, by two application examples of pattern recognition and function approximation.
The current Grover quantum searching algorithm cannot identify the difference in importance of the search targets when it is applied to an unsorted quantum database, and the probability for each search target is equal...
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The current Grover quantum searching algorithm cannot identify the difference in importance of the search targets when it is applied to an unsorted quantum database, and the probability for each search target is equal. To solve this problem, a Grover searching algorithm based on weighted targets is proposed. First, each target is endowed a weight coefficient according to its importance. Applying these different weight coefficients, the targets are represented as quantum superposition states. Second, the novel Grover searching algorithm based on the quantum superposition of the weighted targets is constructed. Using this algorithm, the probability of getting each target can be approximated to the corresponding weight coefficient, which shows the flexibility of this algorithm. Finally, the validity of the algorithm is proved by a simple searching example.
Similar to the shape description using Mexican Hat Wavelet functions we present in this paper the derivation of object descriptors using Haar Wavelets. The derivation is based on the continuous wavelet transformation ...
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ISBN:
(纸本)1424417511
Similar to the shape description using Mexican Hat Wavelet functions we present in this paper the derivation of object descriptors using Haar Wavelets. The derivation is based on the continuous wavelet transformation of an angle function using the Haar function as mother wavelet. The angle function which represents a given object shape is derived from the extracted contour polygon by computing the angle differences between the angles at every position on the contour and the angle at the starting point. This angle function is periodical but with 2 offset and can be normalized in order to be independent of the object's size, it's position and orientation. The angle function depends only on the starting point on the given contour. Moreover, the used angle function doesn't include any singularity which might arise due to object rotations. The derived Wavelet descriptors were used in an agricultural application to recognize weed species. The paper presents in this context some derived results as well as possible solution for the problem of starting point.
This paper proposes a robust algorithm for detecting interest points based on the NonsubSampled Contourlet Transform (NSCT). The NSCT provides multiscale decomposition with directional filters at each scale. Furthermo...
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ISBN:
(纸本)9780769534404
This paper proposes a robust algorithm for detecting interest points based on the NonsubSampled Contourlet Transform (NSCT). The NSCT provides multiscale decomposition with directional filters at each scale. Furthermore, NSCT is very efficient in extracting the geometric information of images and therefore it has very good feature localization. The NSCT-based point detector is compared to the widely used Harris and Difference of Gaussian (DoG) interest point detectors. The experimental results reveal the robustness of the proposed algorithm to rotation, scale and viewpoint changes.
The paper intends to present a modeling philosophy, that allows a global view of a generic manufacturing enterprise behavior, combining managerial and control approaches. The main objective of the assessment is to des...
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In this paper, we study the servomechanism problem for positive LTI systems. In particular, we consider the robust servomechanism problem of nonnegative constant reference signals for stable SISO positive LTI systems ...
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Wheelchair on two wheels is an interesting and challenging control problem. The challenge is in the design and implementation of suitable control strategies for a two wheeled wheelchair to perform comparably similar t...
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ISBN:
(纸本)9780889867116
Wheelchair on two wheels is an interesting and challenging control problem. The challenge is in the design and implementation of suitable control strategies for a two wheeled wheelchair to perform comparably similar to normal four wheeled wheelchair. A wheelchair on two wheels is expected not to take much space during mobility as compared to when it is on four wheels. Moreover, disabled people are encouraged and expected to do most things that others can do and hence lead an independent life. Thus, wheelchairs on two wheels are needed for disabled persons to perform some of the essential tasks in their living and work environments. In this research a model of the standard wheelchair is developed as a test and verification platform using Visual Nastran software. Novel fuzzy logic control strategies are designed for lifting up the chair and maintaining stability and balance while on two wheels. Simulation results of the proposed control strategy are presented and discussed.
Based on the delay-independent rule, the problem of optimal guaranteed cost control for a class of Takagi-Sugeno (T-S) fuzzy descriptor systems with time-varying delay is studied. A linear quadratic cost function is...
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Based on the delay-independent rule, the problem of optimal guaranteed cost control for a class of Takagi-Sugeno (T-S) fuzzy descriptor systems with time-varying delay is studied. A linear quadratic cost function is considered as the performance index of the closed-loop system. Sufficient conditions for the existence of guaranteed cost controllers via state feedback are given in terms of linear matrix inequalities (LMIs), and the design of an optimal guaranteed cost controller can be reduced to a convex optimization problem. It is shown that the designed controller not only guarantees the asymptotic stability of the closed-loop fuzzy descriptor delay system, but also provides an optimized upper bound of the guaranteed cost. At last, a numerical example is given to illustrate the effectiveness of the proposed method and the perfect performance of the optimal guaranteed cost controller.
An efficient distributed algorithm for mobile nodes of wireless sensor network (WSN) is proposed. A smart mobile robot is designed as the special node of WSN, and the nodes of WSN are deployed in the environment as si...
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ISBN:
(纸本)9780819473622
An efficient distributed algorithm for mobile nodes of wireless sensor network (WSN) is proposed. A smart mobile robot is designed as the special node of WSN, and the nodes of WSN are deployed in the environment as signposts for the robot to follow. We use the RSSI value between the robot and other static nodes as the input of the navigation control system. The mobile robot state and navigation space are denoted by the RSSI potential field. Navigation directions are computed by using fuzzy logic method. To reduce the communication expense, each node within one hop communication range of robot is a distributed navigation unites. Then the fuzzy logic control centre will collect the control outputs from every beacon nodes and calculate the final outputs for mobile robot based on data fusion. The experimental results confirm that the navigation system based on WSN successfully achieved their assigned tasks.
This paper proposes an optimal control method for a 10 degree of freedom (DOF) biped robot with stable walking gait. The biped robot is modeled as a 3D inverted pendulum. From dynamic model of the 3D inverted pendulum...
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