With the aim to extend the versatility and adaptability of robots in complex environments, a novel multi-modal flying and walking robot is presented. The robot consists of a flying wing with adaptive morphology that can perform both long distance fli...
This paper establishes a bio-economic singular Markovian jump model by considering the price of the commodity as a Markov chain. The controller is designed for this system such that its biomass achieves the specified range with the least cost in a fi...
IEEE transactions on neural networks and learning systems
Jan 15, 2015
A secondary delay partitioning method is proposed to study the stability problem for a class of recurrent neural networks (RNNs) with time-varying delay. The total interval of the time-varying delay is first divided into two parts, and then each part...
IEEE transactions on neural networks and learning systems
Jan 14, 2015
Learning in multilayer neural networks (MNNs) relies on continuous updating of large matrices of synaptic weights by local rules. Such locality can be exploited for massive parallelism when implementing MNNs in hardware. However, these update rules r...
SAR and QSAR in environmental research
Jan 14, 2015
P-glycoprotein (P-gp) is an ATP binding cassette (ABC) transporter that helps to protect several certain human organs from xenobiotic exposure. This efflux pump is also responsible for multi-drug resistance (MDR), an issue of the chemotherapy approac...
Numerous algorithms have been proposed to allow legged robots to learn to walk. However, most of these algorithms are devised to learn walking in a straight line, which is not sufficient to accomplish any real-world mission. Here we introduce the Tra...
The combination of particle jamming and pneumatics allows the simultaneous control of shape and mechanical properties in a tactile display. A hollow silicone membrane is molded into an array of thin cells, each filled with coffee grounds such that ad...
Imitation and learning from humans require an adequate sensorimotor controller to learn and encode behaviors. We present the Dynamic Muscle Perception-Action(DM-PerAc) model to control a multiple degrees-of-freedom (DOF) robot arm. In the original Pe...
IEEE transactions on neural networks and learning systems
Jan 6, 2015
In this paper, the problem of energy-to-peak state estimation for a class of discrete-time Markov jump recurrent neural networks (RNNs) with randomly occurring nonlinearities (RONs) and time-varying delays is investigated. A practical phenomenon of n...
IEEE transactions on neural networks and learning systems
Jan 6, 2015
This paper is concerned with the passivity analysis for switched neural networks subject to stochastic disturbances and time-varying delays. First, using the multiple Lyapunov functions method, a state-dependent switching law is designed to present a...
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