Aiming at the characters of compressive sensing and genetic algorithm (GA), an adaptive image recovery method is proposed in this paper. Compressive sensing can capture and represent compressible signal at a rate belo...
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Aiming at the characters of compressive sensing and genetic algorithm (GA), an adaptive image recovery method is proposed in this paper. Compressive sensing can capture and represent compressible signal at a rate below the Nyquist rate, and it is possible to reconstruct signals accurately and sometimes even exactly from far fewer data than what is usually considered necessary via using an optimization process which is broadly applied in compressive imaging. GA is global numerical-optimization method which works well in the problem of optimization. Therefore, the new method proposed in this paper combines advantages of compressive sensing and GA which can adaptively look for optimal solution to ensure the best recovery performance. The experiments show that the new method not only has better recovery quality and higher PSNRs, but also can effectively avoid the premature convergence problem and achieve optimization steadily.
For wireless sensor network (WSN), in order to solve the problem which the ETBG have too many cluster heads and these cluster heads distribute too concentrated, a hierarchical clustering algorithm based on energy and ...
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Video streaming over mesh networks operates under stringent network resource constraints, with a large number of video sessions competing for limited network resources. In this work, we aim to establish so-called reso...
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Affective virtual human is considered to one of the hotspots in the field of virtual human-computer interaction. First, the software platform of the management system has been designed, and the virtual human emotional...
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Aiming at the existing problem and the characteristics of teaching basketball technique and tactics, this paper presents a reasonable method of applying computer-Assisted Instruction to the process of teaching basketb...
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In this paper, the vsaUT-II, a novel rotational variable stiffness actuator, is presented. As the other designs in this class of actuation systems, the vsaUT-II is characterized by the property that the output stiffne...
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We introduce a two-step face hallucination frame work as one of classifying among sparse residual compensation model. In the first step, the optimal coefficients of the interpolated training images are used to constru...
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We introduce a two-step face hallucination frame work as one of classifying among sparse residual compensation model. In the first step, the optimal coefficients of the interpolated training images are used to construct a global face image. In the second step, a class of priors is computed based on mixing a set of linear priors related to dissimilar priors. The blocks of coefficients are considered to find the sparse mixing weights. In order to find the best improved information of the face image in the residual compensation of step-two, a sparse signal representation is considered over coefficients in a frame. Finally, we obtain a hallucinated face image by integrating these two steps. The extensive experiments on publicly available database show the effectiveness of the framework.
A matrix-multiplication based multi-secret images sharing scheme is proposed by combining shamir's secret sharing scheme and two-variable one-way functions. The scheme uses the selected seed to generate random mat...
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A matrix-multiplication based multi-secret images sharing scheme is proposed by combining shamir's secret sharing scheme and two-variable one-way functions. The scheme uses the selected seed to generate random matrix, and then uses the matrix to share secret images based on matrix multiplication. In this scheme, the seed is shared among participants by using shamir's secret sharing scheme, which can reduces public information compared with other scheme which is based on matrix multiplication. Two-variable one-way functions are applied to ensure the security and realize multiuse of the scheme. The participants can share multi-secret images by their pseudo-secret rather than their secret share. Experiment shows that the proposed scheme is security and has a good compression rate for image encryption.
Recent advances in neuroscience and robotics have allowed initial demonstrations of brain-computer interfaces (BCIs) for controlling wheeled and humanoid robots. However, further advances have proved challenging due t...
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ISBN:
(纸本)9781467314053
Recent advances in neuroscience and robotics have allowed initial demonstrations of brain-computer interfaces (BCIs) for controlling wheeled and humanoid robots. However, further advances have proved challenging due to the low throughput of the interfaces and the high degrees-of-freedom (DOF) of the robots. In this paper, we build on our previous work on Hierarchical BCIs (HBCIs) which seek to mitigate this problem. We extend HBCIs to allow training of arbitrarily complex tasks, with training no longer restricted to a particular robot state space (such as Cartesian space for a navigation task). We present two algorithms for learning command hierarchies by automatically extracting patterns from a user's command history. The first algorithm builds an arbitrary-level hierarchical structure (a "control grammar") whose elements can represent skills, whole tasks, collections of tasks, etc. The user "executes" single symbols from this grammar, which produce sequences of lower-level commands. The second algorithm, which is probabilistic, also learns sequences which can be executed as high-level commands, but does not build an explicit hierarchical structure. Both algorithms provide a de facto form of dictionary compression, which enhances the effective throughput of the BCI. We present results from two human subjects who successfully used the hierarchical BCI to control a simulated PR2 robot using brain signals recorded non-invasively through electroencephalography (EEG).
A person-computer ensemble system is one of time concerned cooperative systems,which performs secondo(the second part)in an ensemble played by a computer-controlled piano cooperating with primo(the leading part)pl...
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A person-computer ensemble system is one of time concerned cooperative systems,which performs secondo(the second part)in an ensemble played by a computer-controlled piano cooperating with primo(the leading part)played by a person *** is a good example of intelligent realtime programs appropriate for formal verification and analysis. NΣ-labeled calculus is a formal system in order to describe such systems including time-concerned recognition,knowledge, belief and decision of persons or computer programs together with related external physical or logical phenomena. In the realtime performance of music,to determine which key is played just now by the person performer,the matching algorithm between the score and the realtime input from the person performer is *** there are some mistouching, *** an incorrect key,or other mistake,error,etc.,and if the program does not detect and correct such errors,it does not determine which note is performed just now and which note of the secondo will be done just after now,and hence,it cannot control the performance ***,the matching method including correction of these mistouches is essential.A simple but very efficient matching method with error detecting has been already developed and presented by the authors. In this paper,the formal representation of the program and its formal specification satisfied by the program written and verified in the calculus are introduced.
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