Motivation: Submodular optimization, a discrete analogue to continuous convex optimization, has been used with great success in many fields but is not yet widely used in biology. We apply submodular optimization to the problem of removing redundancy in protein sequence data sets. This is a common step in many bioinformatics and structural biology workflows, including creation of non-redundant t...

In this paper, it is pointed-out that inverse problems arising in nonlinear control systems design such as state reconstruction and/or parameter estimation are naturally redundant. It is also shown that this redundancy can be used to enhance avoiding singularity heuristics. Some related algorithms are discussed and illustrated on a simple example of chemical reactors. These algorithms can be ad...

Priority Encoding Transmission (PET) is an encoding scheme which provides multiple levels of redundancy in order to protect the different contents of a data set according to their importance. The task of optimally assigning redundancies for the PET encoding scheme is investigated for the special case of MPEG-1 encoded video sequences. The prerequisites for this optimization problem and the way ...

Mediators Vasilis Vassalos Computer Science Department Stanford University Stanford, CA 94305 [email protected] Yannis Papakonstantinou Dept. of Computer Science and Engineering University of California, San Diego La Jolla, CA 92093 [email protected]

Image fusion in high-resolution aerial imagery poses a challenging problem due to fine details and complex textures. In particular, color image fusion by using virtual orthographic cameras offers a common representation of overlapping yet perspective aerial images. This paper proposes a variational formulation for a tight integration of redundant image data showing urban environments. We introd...

The Redundancy Allocation Problem (RAP) is well-known in the field of reliability optimization. In this paper, RAP investigated assuming that distribution time to failure components has form an Erlang with a time-dependent rate parameter and considering choice redundancy for each subsystem can be none, active, standby or mixed. A genetic algorithm used solve problem optimal allocation. To analy...

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Under the given system weight constraint, we consider the problem of maximizing the system lifetime and minimizing the system cost. The lifetimes of components in the system are characterized by type-2 fuzzy variables. The numbers of redundant elements of each components are the decision variables. We use the reduction methods to reduce the type-2 fuzzy lifetimes. Then, we propose a goal progra...

The curse of dimensionality is a well-known problem in pattern recognition in which the number of patterns is smaller than the number of features in the datasets. Often, many of the features are irrelevant and redundant for the classification tasks. Therefore, the feature selection becomes an essential technique to reduce the dimensionality of the datasets. In this paper, unsupervised and multi...

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