Based on the mechanisms of immunodominance and clonal selection theory, we propose a new multiobjective optimization algorithm, immune dominance clonal multiobjective algorithm (IDCMA). IDCMA is unique in that its f...
详细信息
Based on the mechanisms of immunodominance and clonal selection theory, we propose a new multiobjective optimization algorithm, immune dominance clonal multiobjective algorithm (IDCMA). IDCMA is unique in that its fitness values of current dominated individuals are assigned as the values of a custom distance measure, termed as Ab-Ab affinity, between the dominated individuals and one of the nondominated individuals found so far. According to the values of Ab-Ab affinity, all dominated individuals (antibodies) are divided into two kinds, subdominant antibodies and cryptic antibodies. Moreover, local search only applies to the subdominant antibodies, while the cryptic antibodies are redundant and have no function during local search, but they can become subdominant (active) antibodies during the subsequent evolution. Furthermore, a new immune operation, clonal proliferation is provided to enhance local search. Using the clonal proliferation operation, IDCMA reproduces individuals and selects their improved maturated progenies after local search, so single individuals can exploit their surrounding space effectively and the newcomers yield a broader exploration of the search space. The performance comparison of IDCMA with MISA, NSGA-Ⅱ, SPEA, PAES, NSGA, VEGA, NPGA, and HLGA in solving six well-known multiobjective function optimization problems and nine multiobjective 0/1 knapsack problems shows that IDCMA has a good performance in converging to approximate Pareto-optimal fronts with a good distribution.
This paper introduced a novel high performance algorithm and VLSI architectures for achieving bit plane coding (BPC) in word level sequential and parallel mode. The proposed BPC algorithm adopts the techniques of co...
详细信息
This paper introduced a novel high performance algorithm and VLSI architectures for achieving bit plane coding (BPC) in word level sequential and parallel mode. The proposed BPC algorithm adopts the techniques of coding pass prediction and parallel & pipeline to reduce the number of accessing memory and to increase the ability of concurrently processing of the system, where all the coefficient bits of a code block could be coded by only one scan. A new parallel bit plane architecture (PA) was proposed to achieve word-level sequential coding. Moreover, an efficient high-speed architecture (HA) was presented to achieve multi-word parallel coding. Compared to the state of the art, the proposed PA could reduce the hardware cost more efficiently, though the throughput retains one coefficient coded per clock. While the proposed HA could perform coding for 4 coefficients belonging to a stripe column at one intra-clock cycle, so that coding for an NxN code-block could be completed in approximate N2/4 intra-clock cycles. Theoretical analysis and experimental results demonstrate that the proposed designs have high throughput rate with good performance in terms of speedup to cost, which can be good alternatives for low power applications.
On visual tracking, a particle filter algorithm was presented to track a moving target under clutter environment which can deal with rotation, scale changes, variations in the light source and partial occlusions. So i...
详细信息
On visual tracking, a particle filter algorithm was presented to track a moving target under clutter environment which can deal with rotation, scale changes, variations in the light source and partial occlusions. So it can track the target with robustness. The proposed method was based on particle filter, integrated with color histogram in the measurement model, and the system model was second order autoregressive process. The algorithm took into account the latest observations and the tracked target can be rigid or non-rigid. Also the method can run in real-time. The experimental results confirm that the method is effective even when the monocular camera is moving and the target object is partially occluded in a clutter background.
Aero-optic effects cause distortions, including blurring, vibration, deformation and spatial shifting, of the objects in the image obtained by the infra-red sensor. Contributions of this paper are in the following two...
详细信息
A transient, six-cylinder diesel engine model for cold test has been developed for analyzing the engine fault through the engine torque curve. The model is based on physically working cycle, thermodynamic theory and d...
详细信息
A transient, six-cylinder diesel engine model for cold test has been developed for analyzing the engine fault through the engine torque curve. The model is based on physically working cycle, thermodynamic theory and dynamics mechanism. The simulation of this model, implemented on Matlab/Simulink, can not only achieve engine faults detection before hot test, but also indicate different causes of engine faults, such as initial phase change, intake valve closing-time delay, and so on. It is shown that the diesel engine model for cold test proves its significance to improving cold test technology.
To control the mobile robot with the surrounding information is the essential method to realize the intelligence and automatic moving. The vision information is the most important way to perceive the environment for t...
详细信息
To control the mobile robot with the surrounding information is the essential method to realize the intelligence and automatic moving. The vision information is the most important way to perceive the environment for the mobile robot. This paper presents an essential camera calibration technique for mobile robot, which is based on Pioneer II experiment platform. The technique includes transformation of coordinates system for vision system, the model and principle of image formation, camera distortion calibration. Because of non-linear distortion of camera, algorithm with optimizing operators is presented to improve calibration precision. We verify the validity and feasibility of the algorithm through experiment.
Several neutrosophic combination rules based on the Dempster-Shafer theory (DST) and Dezert-Smarandache theory (DSmT) are presented in this study. The new information fusing approaches proposed the neutrosophic belief...
详细信息
In this paper, a variant of support vector novelty detection (SVND) with dot product kernels is presented for non-spherical distributed data. Firstly we map the data in input space into a reproducing kernel Hilbert sp...
详细信息
In this paper, a variant of support vector novelty detection (SVND) with dot product kernels is presented for non-spherical distributed data. Firstly we map the data in input space into a reproducing kernel Hilbert space (RKHS) by using kernel trick. Secondly we perform whitening process on the mapped data using kernel principal component analysis (KPCA). Finally, we adopt SVND method to train and test whitened data. Experiments were performed on artificial and real-world data.
Liquid State Machine (LSM) is a newly developed computational model with many interesting properties. It has great advantages of dealing with biologic computing when compared to the traditional computational model. In...
Liquid State Machine (LSM) is a newly developed computational model with many interesting properties. It has great advantages of dealing with biologic computing when compared to the traditional computational model. In this paper, the LSM was used to deal with the direction classification problem of the spike series which were distilled from the neurons in motor cortex of a monkey. In the output layer, a linear regression and back-propagation are employed as the training algorithms. Compare to outcomes of the two algorithms, it is showed that ideal classification results were derived when using BP as the training algorithm.
暂无评论