Which to use? - microarray data analysis in input and output data processing

Input/output versus output-only data processing for structural identification—Application to in-flight data analysis

The problem of structural model identification under both known and unknown input excitations, is addressed. In-flight data analysis is an important instance of that problem. Input/output and output-only eigenstructure identification methods are described and compared, within two classes of methods: subspace-based and prediction error. In particular, different types of relevant projections for ...

Input congestion, technical ineciency and output reduction in fuzzy data envelopment analysis

During the last years, the concept of input congestion and technical ineff-ciency in data envelopment analysis (DEA), have been investigated by manyresearchers. The motivation of this paper is to present models which obtain thedecreased output value due to input congestion and technical ineciency. More-over, we extend the models to estimate input congestion, technical ineciencyand output reduct...

Microarray Data Processing and Analysis

DNA arrays technologies make possible the monitoring of changes in the expression patterns of thousands of genes. The analysis of such data has become a computationally-intensive task that requires technological developments at various stages, from the design of the array, to image analysis, database storage, data processing and clustering and information extraction. Here a review of the curren...

Multiple Fuzzy Regression Model for Fuzzy Input-Output Data

A novel approach to the problem of regression modeling for fuzzy input-output data is introduced.In order to estimate the parameters of the model, a distance on the space of interval-valued quantities is employed.By minimizing the sum of squared errors, a class of regression models is derived based on the interval-valued data obtained from the $alpha$-level sets of fuzzy input-output data.Then,...

cDNA Microarray Data Normalization