IEEE transactions on neural networks and learning systems
Jan 30, 2015
This paper develops a neural network architecture and a new processing method for solving in real time, the nonlinear equality constrained multiobjective optimization problem (NECMOP), where several nonlinear objective functions must be optimized in ...
Early brain connectivity development consists of multiple stages: birth of neurons, their migration and the subsequent growth of axons and dendrites. Each stage occurs within a certain period of time depending on types of neurons and cortical layers....
We present a novel interactive segmentation framework incorporating a priori knowledge learned from training data. The knowledge is learned as a structured patch model (StPM) comprising sets of corresponding local patch priors and their pairwise spat...
Clinical pharmacology in drug development
Jan 26, 2015
PURPOSE: Rucaparib is a potent Poly (ADP-ribose) Polymerase (PARP) inhibitor currently under clinical development. The objectives of this analysis were to establish population PK and PK/PD models for rucaparib, and to evaluate the predictability of P...
Journal of computational neuroscience
Jan 21, 2015
In this paper we provide a general methodology for systematically reducing the dynamics of a class of integrate-and-fire networks down to an augmented 4-dimensional system of ordinary-differential-equations. The class of integrate-and-fire networks w...
Computer methods and programs in biomedicine
Jan 21, 2015
BACKGROUND: There is a growing demand for women to be classified into different risk groups of developing breast cancer (BC). The focus of the reported work is on the development of an integrated risk prediction model using a two-level fuzzy cognitiv...
Recently, there have been several attempts to replicate theory of mind, which explains how humans infer the mental states of other people using multiple sensory input, with artificial systems. One example of this is a robot that observes the behavior...
IEEE transactions on neural networks and learning systems
Jan 20, 2015
This paper investigates the stochastic synchronization problem for Markovian hybrid coupled neural networks with interval time-varying mode-delays and random coupling strengths. The coupling strengths are mutually independent random variables and the...
Attractor models are simplified models used to describe the dynamics of firing rate profiles of a pool of neurons. The firing rate profile, or the neuronal activity, is thought to carry information. Continuous attractor neural networks (CANNs) descri...
This paper is concerned with the resilient H∞ filtering problem for a class of discrete-time Markov jump neural networks (NNs) with time-varying delays, unideal measurements, and multiplicative noises. The transitions of NNs modes and desired mode-de...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.