Digital implementations of control laws typically involve discretization with respect to both time and space, and a control law that can achieve a task at coarser levels of discretization can be said to require less control attention, and also reduce...
In this paper, the problem of passivity analysis is studied for memristor-based uncertain neural networks with leakage and time-varying delays. By combining differential inclusions with set-valued maps, the system of memristive neural networks is cha...
As robots become more involved in underwater operations, understanding underwater contact sensing with compliant systems is fundamental to engineering useful haptic interfaces and vehicles. Despite knowledge of contact sensation in air, little is kno...
IEEE transactions on bio-medical engineering
Oct 1, 2015
GOAL: In this study, we defined a realistic cerebellar model through the use of artificial spiking neural networks, testing it in computational simulations that reproduce associative motor tasks in multiple sessions of acquisition and extinction.
This paper is concerned with the finite-time synchronization (FTS) issue of switched coupled neural networks with discontinuous or continuous activations. Based on the framework of nonsmooth analysis, some discontinuous or continuous controllers are ...
Pneumatic artificial muscles (PAMs) are actuators known for their high power to weight ratio, natural compliance and light weight. Due to these advantages, PAMs have been used for orthotic devices and robotic limbs. Small scale PAMs have the same adv...
Cephalopods (i.e., octopuses and squids) are being looked upon as a source of inspiration for the development of unmanned underwater vehicles. One kind of cephalopod-inspired soft-bodied vehicle developed by the authors entails a hollow, elastic shel...
The three-phase shift between line current and phase voltage of induction motors can be used as an efficient fault indicator to detect and locate inter-turn stator short-circuit (ITSC) fault. However, unbalanced supply voltage is one of the contribut...
For the 2014 i2b2/UTHealth de-identification challenge, we introduced a new non-parametric Bayesian hidden Markov model using a Dirichlet process (HMM-DP). The model intends to reduce task-specific feature engineering and to generalize well to new da...
Journal of computational neuroscience
Sep 24, 2015
Neuronal adaptation is the intrinsic capacity of the brain to change, by various mechanisms, its dynamical responses as a function of the context. Such a phenomena, widely observed in vivo and in vitro, is known to be crucial in homeostatic regulatio...
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