/pdf/convex-analysisnoer-san-nojin-zhan-nituite-5dl2rbmoyr.pdf

Convex Analysisの二,三の進展について

It is shown that, particularly for terrestrial cellular telephony, the interference-suppression feature of CDMA (code division multiple access) can result in a many-fold increase in capacity over analog and even over competing digital techniques. A single-cell system, such as a hubbed satellite network, is addressed, and the basic expression for capacity is developed. The corresponding expressions for a multiple-cell system are derived. and the distribution on the number of users supportable per cell is determined. It is concluded that properly augmented and power-controlled multiple-cell CDMA promises a quantum increase in current cellular capacity. >

On the capacity of a cellular CDMA system

This paper presents control and coordination algorithms for groups of vehicles. The focus is on autonomous vehicle networks performing distributed sensing tasks where each vehicle plays the role of a mobile tunable sensor. The paper proposes gradient descent algorithms for a class of utility functions which encode optimal coverage and sensing policies. The resulting closed-loop behavior is adaptive, distributed, asynchronous, and verifiably correct.

Coverage control for mobile sensing networks

Thank you very much for downloading flow the psychology of optimal experience. As you may know, people have search numerous times for their chosen readings like this flow the psychology of optimal experience, but end up in infectious downloads. Rather than reading a good book with a cup of tea in the afternoon, instead they juggled with some harmful bugs inside their desktop computer. flow the psychology of optimal experience is available in our digital library an online access to it is set as public so you can get it instantly. Our digital library saves in multiple countries, allowing you to get the most less latency time to download any of our books like this one. Merely said, the flow the psychology of optimal experience is universally compatible with any devices to read.

Flow The Psychology Of Optimal Experience

Thank you very much for downloading biomechanics and motor control of human movement. Maybe you have knowledge that, people have search hundreds times for their favorite books like this biomechanics and motor control of human movement, but end up in infectious downloads. Rather than enjoying a good book with a cup of tea in the afternoon, instead they juggled with some malicious virus inside their laptop.

Biomechanics And Motor Control Of Human Movement

This paper mainly focuses on the trajectory tracking control of a lower extremity rehabilitation robot during passive training process of patients. Firstly, a mathematical model of the rehabilitation robot is introduced by using Lagrangian analysis. Then, a model based computed-torque control scheme is designed to control the constrained four-link robot (with patient's foot fixed on robot's end-effector) to track a predefined trajectory. Simulation results are provided to illustrate the effectiveness of the proposed model based computed-torque algorithm. In the simulation, a multi-body dynamics and motion software named ADAMS is used. The combined simulation of ADAMS and MATLAB is able to produce more realistic results of this complex integrated system.

Model based control of a rehabilitation robot for lower extremities

In fighting the coronary heart diseases, percutaneous coronary intervention is proved to be a powerful and reliable clinical procedure in the modern catheterization labs all over the world. Due to its minimally invasive characteristics, the procedure must be performed in the image-guided way, which makes this important skill very difficult to learn. To make the learning more accessible, a computer-aided surgical simulator is planned to be implemented in our lab. For now, the prototyping model is completed and the further validation is being conducted. In implementing the virtual anatomic environment, we aim to provide the trainee an intuitive visual effect so that the models of the organs bear resemblance to their counterpart of the human's. Besides the blood vessels per se, the surrounding organs seen in the real surgery also need to be visualized during the simulation. The heart is undoubtedly the most critical one among them. The segmentation of the heart is a challenging task because of the noisy and indistinct boundaries of the heart in the images due to the natural heart beating during the image acquisition. In this paper, an approach based on the active contours method is developed to fulfill this job. The experimental results demonstrate the effectiveness of our approach.

https://ieeexplore.ieee.org/iel7/6882077/6895198/06896411.pdf

Segmentation and visualization of the heart region for 3-D simulation of coronary intervention procedures

The Fifth International Symposium on Neural Networks (ISNN’08) was held in Beijing, China, between September 24 and 28, 2008. The ISNN’08 was a great success and covered broad topics of neural network research and applications in diverse fields. As a continuation of this successful conference, we organized this special issue of Neural Computing and Applications on ‘‘computational intelligence for optimization and control’’, with 12 selected quality papers from ISNN’08. The theme of this special issue is to present the state-of-the-art developments in recent research focusing on neural networks for optimization, modeling and control. Over the past decades, many important theoretical and application researches were developed in the area of neural networks and learning systems. Although the understanding of natural intelligence behavior and design brain-like intelligent machines still remain a challenging topic, neural networks have been proven successful in many real-world applications. To this end, the selected 12 papers in this special issue can be categorized into four major sections under this theme. The first section is focused on intelligent algorithms and optimization. For instance, Hong Zhang and Masumi Ishikawa presented particle swarm optimization with diversive curiosity (PSO/DC). The obtained experimental results basically accord with the findings in psychology, i.e., diversive curiosity being prone to exploration and anxiety. Traffic congestion identification is a popular research topic of intelligent transport systems (ITS). Identification rate of existing methods usually cannot meet the practical requirements. To improve the identification rate and reduce the computation cost, Zhanquan Sun et al. proposed a novel intelligent identification method. The paper by Michael M. Li et al. investigated two different intelligent techniques—the neural network method and the simulated annealing algorithm for solving the inverse problem of Rutherford backscattering with noisy data. The paper by André Cyr et al. presented a software simulator designed to explore the computational power of pulsed coding at the level of small cognitive systems. The second section is focused on information fusion. For instance, Yongwei Li et al. discussed a structure of fault information fusion system, in which BP neural network was used as a classifier to distinguish different fault types. Fiber Bragg grating sensing technique was applied to monitor the high-voltage electric equipment in order to overcome the harsh monitoring environment. The paper by Ning Chen et al. presented a novel neural network approach which combines modified probabilistic neural network and D–S evidence theory (PNN–DS) for target classification problems. This scheme was based on the supervised learning, where the posterior probabilities are achieved and a primary classification decision is made by a PNN structure. The third section is focused on neural modeling. For instance, Vishy Karri and Tien Ho investigated the use of Z.-G. Hou (&) Key Laboratory of Complex Systems and Intelligence Science, Institute of Automation, The Chinese Academy of Sciences, P.O. Box 2728, 100190 Beijing, China e-mail: zengguang.hou@ia.ac.cn

Editorial to special issue: computational intelligence for optimization, modeling and control

This paper mainly focuses on the modeling of oil well pressure data compensation system (OWPCS) based on Neural Networks (NN). Firstly, the operational principle and configuration of OWPCS is described. Then the currently widely used modeling method for OWPCS is given, and its limitations and disadvantages are also illustrated. Secondly, in order to solve the OWPCS modeling problem more reasonably, a new approach based on Neural Network is proposed. Thirdly, the feasibility of using NN to solve this problem is analyzed, and a three-layer BP network is constructed to testify the new modeling method. Fourthly, considering the defect of BP learning algorithm and the special application environment of OWPCS, some improvements are given. Finally, experiment results are presented to show the reasonableness and effectiveness of the new method.

Neural network based modeling for oil well pressure data compensation system

/pdf/semg-and-knn-based-human-motion-intention-recognition-for-4lfyfxycc5.pdf

Zeng-Guang Hou

Papers

Model based control of a rehabilitation robot for lower extremities

Segmentation and visualization of the heart region for 3-D simulation of coronary intervention procedures

Editorial to special issue: computational intelligence for optimization, modeling and control

Neural network based modeling for oil well pressure data compensation system

SEMG and KNN Based Human Motion Intention Recognition for Active and Safe Neurorehabilitation.