Computational intelligence and neuroscience
Feb 1, 2017
Real-time path planning for autonomous underwater vehicle (AUV) is a very difficult and challenging task. Bioinspired neural network (BINN) has been used to deal with this problem for its many distinct advantages: that is, no learning process is need...
This paper studies delay-dependent exponential dissipative and l - l filtering problems for discrete-time switched neural networks (DSNNs) including time-delayed states. By introducing a novel discrete-time inequality, which is a discrete-time versio...
We investigate a hierarchical approach to robot control inspired by joint-level control in animals. The method combines a high-level controller, consisting of an artificial neural network (ANN), with joint-level controllers based on digital muscles. ...
Neural networks : the official journal of the International Neural Network Society
Jan 30, 2017
Object class segmentation is a computer vision task which requires labeling each pixel of an image with the class of the object it belongs to. Deep convolutional neural networks (DNN) are able to learn and take advantage of local spatial correlations...
Neural networks : the official journal of the International Neural Network Society
Jan 30, 2017
This paper focuses on stability analysis for neural networks systems with time-varying delays. A more general auxiliary function-based integral inequality is established and some improved delay-dependent stability conditions formulated in terms of li...
The use of echogenic liposomes to deliver chemotherapeutic agents for cancer treatment has gained wide recognition in the last 20 years. Cancerous cells can develop multiple drug resistance (MDR), in part, due to the drop in concentration of chemothe...
Chinese liquors are internationally well-known fermentative alcoholic beverages. They have unique flavors attributable to the use of various bacteria and fungi, raw materials, and production processes. Developing a novel, rapid, and reliable method t...
Computational and mathematical methods in medicine
Jan 30, 2017
Computational models are useful tools to study the biomechanics of human joints. Their predictive performance is heavily dependent on bony anatomy and soft tissue properties. Imaging data provides anatomical requirements while approximate tissue prop...
Neural networks : the official journal of the International Neural Network Society
Jan 28, 2017
Although Hebbian learning has long been a key component in understanding neural plasticity, it has not yet been successful in modeling modulatory feedback connections, which make up a significant portion of connections in the brain. We develop a new ...
Mechanistic modeling has been repeatedly successfully applied in process development and control of protein chromatography. For each combination of adsorbate and adsorbent, the mechanistic models have to be calibrated. Some of the model parameters, s...
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