/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

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Flow The Psychology Of Optimal Experience

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Biomechanics And Motor Control Of Human Movement

Multiple kernel learning (MKL) aims at simultaneously optimizing kernel weights while training the support vector machine (SVM) to get satisfactory classification or regression results. Recent publications and developments based on SVM have shown that by using MKL one can enhance interpretability of the decision function and improve classifier performance, which motivates researchers to explore the use of homogeneous model obtained as linear combination of various types of kernels. In this paper, we show that MKL problems can be solved efficiently by modified projection gradient method and applied for image categorization and object detection. The kernel is defined as a linear combination of feature histogram function that can measure the degree of similarity of partial correspondence between feature sets for discriminative classification, which allows recognition robust to within-class variation, pose changes, and articulation. We evaluate our proposed framework on the ETH-80 dataset for several multi-level image encodings for supervised and unsupervised object recognition and report competitive results.

Image category learning and classification via optimal linear combination of multiple partially matching kernels

The ability of cognition and recognition for complex environment is very important for a real autonomous robot. A new scene analysis method using kernel principal component analysis (PCA) for mobile robot based on multi-sonar-ranger data is put forward. The principle of classification by principal component analysis (PCA), Kernel-PCA, and the BP neural network approach to extract the largest k eigenvectors are introduced briefly. Next PCA, Kernel-PCA and the BP neural network methods are applied in the corridor scene analysis and classification for the mobile robots based on sonar data. At last the experimental results using PCA, Kernel-PCA and the BP neural network are compared and such conclusions are drawn: in common corridor scene classification, the Kernel-PCA method has advantage over the ordinary PCA, and the BP neural network approach can also get satisfactory result.

Scene Analysis for Mobile Robot Based on Multi-Sonar-Ranger Data

Vascular interventional robot is becoming increasingly popular in assisting doctors for the treatment of cardiovascular diseases (CVDs). However, natural manipulations and motion patterns of surgeons in percutaneous coronary intervention (PCI), including finger motion and hand motion, are potentially altered more or less through this solution. Since clinical success is highly dependent on the skills and dexterous manipulation strategies of the surgeons, but these skills and experience remains an underused resource in robot-assisted intervention. In this paper, surface electromyography (sEMG) of surgeons' hand and arm muscles, a feature of manipulation skills in intervention, is acquired to recognize six interventional manipulations with Back-Propagation (BP) neural network. A modified principal component analysis (PCA) is presented to select a sensitive and principal muscle subset for improving the fiexibility of subjects' manipulations. Experimental results show that the sensitive muscle subset with the recognition rate over 90% performs better than the insensitive one, and the sEMG-based BP neural network has the ability to recognize interventional manipulations with a high accuracy.

PCA-based muscle selection for interventional manipulation recognition

Higher-order neural units for image processing and their applications to robot routing problems

A catheter or guide wire manipulating device with two-point-clamping for vascular intervention is provided, comprising a thumb component (3), a forefinger component (4), a driving component (1) and a catheter/guide wire support component (2); the thumb component (3) comprises a pair of rollers (9, 10) configured to advance or retreat the catheter/guide wire; the thumb component (3) is configured to drive the catheter/guide wire to rotate clockwise or counterclockwise through a combination motion of the components; the forefinger component (4) is configured to implement the rotation and the advancement of the catheter/guide wire by moving manually away from the thumb component (3), and returning by a pull force of a spring (27) after being released; the driving component (2) is configured to drive the thumb component (3) and the forefinger component (4); the catheter/guide wire support component comprises a Y adapter fixation configured to install a Y adapter and an entry support configured to support and guide the catheter/guide wire into a mechanism.

Zeng-Guang Hou

Papers

Image category learning and classification via optimal linear combination of multiple partially matching kernels

Scene Analysis for Mobile Robot Based on Multi-Sonar-Ranger Data

PCA-based muscle selection for interventional manipulation recognition

Higher-order neural units for image processing and their applications to robot routing problems

Catheter or guide wire manipulating device with two-point-clamping for vascular intervention