AIMC Topic: Computer Simulation

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Training spiking neural models using artificial bee colony.

Computational intelligence and neuroscience
Spiking neurons are models designed to simulate, in a realistic manner, the behavior of biological neurons. Recently, it has been proven that this type of neurons can be applied to solve pattern recognition problems with great efficiency. However, th...

Spatiotemporal System Identification With Continuous Spatial Maps and Sparse Estimation.

IEEE transactions on neural networks and learning systems
We present a framework for the identification of spatiotemporal linear dynamical systems. We use a state-space model representation that has the following attributes: 1) the number of spatial observation locations are decoupled from the model order; ...

Solving nonlinear equality constrained multiobjective optimization problems using neural networks.

IEEE transactions on neural networks and learning systems
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 ...

Developmental time windows for axon growth influence neuronal network topology.

Biological cybernetics
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....

Structured patch model for a unified automatic and interactive segmentation framework.

Medical image analysis
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...

PARP activity in peripheral blood lymphocytes as a predictive biomarker for PARP inhibition in tumor tissues - A population pharmacokinetic/pharmacodynamic analysis of rucaparib.

Clinical pharmacology in drug development
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...

A reduction for spiking integrate-and-fire network dynamics ranging from homogeneity to synchrony.

Journal of computational neuroscience
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...

An integrated breast cancer risk assessment and management model based on fuzzy cognitive maps.

Computer methods and programs in biomedicine
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...

Inference of other's internal neural models from active observation.

Bio Systems
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...

Mode-Dependent Stochastic Synchronization for Markovian Coupled Neural Networks With Time-Varying Mode-Delays.

IEEE transactions on neural networks and learning systems
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...