AIMC Topic: Algorithms

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Non-divergence of stochastic discrete time algorithms for PCA neural networks.

IEEE transactions on neural networks and learning systems
Learning algorithms play an important role in the practical application of neural networks based on principal component analysis, often determining the success, or otherwise, of these applications. These algorithms cannot be divergent, but it is very...

Consensus-based distributed cooperative learning from closed-loop neural control systems.

IEEE transactions on neural networks and learning systems
In this paper, the neural tracking problem is addressed for a group of uncertain nonlinear systems where the system structures are identical but the reference signals are different. This paper focuses on studying the learning capability of neural net...

Backstepping fuzzy-neural-network control design for hybrid maglev transportation system.

IEEE transactions on neural networks and learning systems
This paper focuses on the design of a backstepping fuzzy-neural-network control (BFNNC) for the online levitated balancing and propulsive positioning of a hybrid magnetic levitation (maglev) transportation system. The dynamic model of the hybrid magl...

A scalable projective scaling algorithm for l(p) loss with convex penalizations.

IEEE transactions on neural networks and learning systems
This paper presents an accurate, efficient, and scalable algorithm for minimizing a special family of convex functions, which have a lp loss function as an additive component. For this problem, well-known learning algorithms often have well-establish...

Learning feature representations with a cost-relevant sparse autoencoder.

International journal of neural systems
There is an increasing interest in the machine learning community to automatically learn feature representations directly from the (unlabeled) data instead of using hand-designed features. The autoencoder is one method that can be used for this purpo...

Measuring physician adherence with gout quality indicators: a role for natural language processing.

Arthritis care & research
OBJECTIVE: To evaluate physician adherence with gout quality indicators (QIs) for medication use and monitoring, and behavioral modification (BM).

["Big data" - large data, a lot of knowledge?].

Praxis
Since a couple of years, the term Big Data describes technologies to extract knowledge from data. Applications of Big Data and their consequences are also increasingly discussed in the mass media. Because medicine is an empirical science, we discuss ...

Automatic Wheezing Detection Based on Signal Processing of Spectrogram and Back-Propagation Neural Network.

Journal of healthcare engineering
Wheezing is a common clinical symptom in patients with obstructive pulmonary diseases such as asthma. Automatic wheezing detection offers an objective and accurate means for identifying wheezing lung sounds, helping physicians in the diagnosis, long-...

[Comparative Efficiency of Algorithms Based on Support Vector Machines for Regression].

Biofizika
Methods of construction of support vector machines do not require additional a priori information and can be used to process large scale data set. It is especially important for various problems in computational biology. The main set of algorithms of...

Dynamic partial reconfiguration implementation of the SVM/KNN multi-classifier on FPGA for bioinformatics application.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Bioinformatics data tend to be highly dimensional in nature thus impose significant computational demands. To resolve limitations of conventional computing methods, several alternative high performance computing solutions have been proposed by scient...