AIMC Topic: Algorithms

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Adaptive optimal control of highly dissipative nonlinear spatially distributed processes with neuro-dynamic programming.

IEEE transactions on neural networks and learning systems
Highly dissipative nonlinear partial differential equations (PDEs) are widely employed to describe the system dynamics of industrial spatially distributed processes (SDPs). In this paper, we consider the optimal control problem of the general highly ...

Quaternion-valued echo state networks.

IEEE transactions on neural networks and learning systems
Quaternion-valued echo state networks (QESNs) are introduced to cater for 3-D and 4-D processes, such as those observed in the context of renewable energy (3-D wind modeling) and human centered computing (3-D inertial body sensors). The introduction ...

Clinical vestibular testing assessed with machine-learning algorithms.

JAMA otolaryngology-- head & neck surgery
IMPORTANCE: Dizziness and imbalance are common clinical problems, and accurate diagnosis depends on determining whether damage is localized to the peripheral vestibular system. Vestibular testing guides this determination, but the accuracy of the dif...

Evaluation of a hospital admission prediction model adding coded chief complaint data using neural network methodology.

European journal of emergency medicine : official journal of the European Society for Emergency Medicine
OBJECTIVE: Our objective was to apply neural network methodology to determine whether adding coded chief complaint (CCC) data to triage information would result in an improved hospital admission prediction model than one without CCC data.

Focus-independent particle size measurement from streak images: a comparison of multivariate methods.

The Analyst
Our laboratories have recently developed a flow-through imaging photometer to characterize and classify fluorescent particles between 3 and 47 μm in size. The wide aperture of the objective lens (0.7 NA) required for measuring spectral fluorescence o...

Human-level control through deep reinforcement learning.

Nature
The theory of reinforcement learning provides a normative account, deeply rooted in psychological and neuroscientific perspectives on animal behaviour, of how agents may optimize their control of an environment. To use reinforcement learning successf...

[The blind source separation method based on self-organizing map neural network and convolution kernel compensation for multi-channel sEMG signals].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
A new method based on convolution kernel compensation (CKC) for decomposing multi-channel surface electromyogram (sEMG) signals is proposed in this paper. Unsupervised learning and clustering function of self-organizing map (SOM) neural network are e...

Comparative analysis of breast cancer detection in mammograms and thermograms.

Biomedizinische Technik. Biomedical engineering
In this paper, we present a system based on feature extraction techniques for detecting abnormal patterns in digital mammograms and thermograms. A comparative study of texture-analysis methods is performed for three image groups: mammograms from the ...