A formal methods approach to pattern synthesis in reaction diffusion systems

Download

index.pdf

Date

2015-02-12

Author

Aydın Göl, Ebru
Belta, Calin

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

199
views

85
downloads

We propose a technique to detect and generate patterns in a network of locally interacting dynamical systems. Central to our approach is a novel spatial superposition logic, whose semantics is defined over the quad-tree of a partitioned image. We show that formulas in this logic can be efficiently learned from positive and negative examples of several types of patterns. We also demonstrate that pattern detection, which is implemented as a model checking algorithm, performs very well for test data sets different from the learning sets. We define a quantitative semantics for the logic and integrate the model checking algorithm with particle swarm optimization in a computational framework for synthesis of parameters leading to desired patterns in reaction-diffusion systems.

Subject Keywords

Semantics, Steady-state, Cost accounting, Pattern recognition, Model checking, Syntactics, Silicon

URI

https://hdl.handle.net/11511/33259

DOI

https://doi.org/10.1109/cdc.2014.7039367

Collections

Department of Computer Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

A Formal Methods Approach to Pattern Recognition and Synthesis in Reaction Diffusion Networks Bartocci, Ezio; Aydın Göl, Ebru; Haghighi, Iman; Belta, Calin (2018-03-01) We introduce a formal framework for specifying, detecting, and generating spatial patterns in reaction diffusion networks. Our approach is based on a novel spatial superposition logic, whose semantics is defined over the quad-tree representation of a partitioned image. We demonstrate how to use rule-based classifiers to efficiently learn spatial superposition logic formulas for several types of patterns from positive and negative examples. We implement pattern detection as a model-checking algorithm and we ...
A visual interactive approach for scenario-based stochastic multi-objective problems and an application Balibek, E.; Köksalan, Mustafa Murat (2012-12-01) In many practical applications of stochastic programming, discretization of continuous random variables in the form of a scenario tree is required. In this paper, we deal with the randomness in scenario generation and present a visual interactive method for scenario-based stochastic multi-objective problems. The method relies on multi-variate statistical analysis of solutions obtained from a multi-objective stochastic problem to construct joint confidence regions for the objective function values. The decis...
Blind Deinterleaving of Signals in Time Series with Self-Attention Based Soft Min-Cost Flow Learning Can, Oğul; Gürbüz, Yeti Ziya; Yildirim, Berkin; Alatan, Abdullah Aydın (2021-01-01) We propose an end-to-end learning approach to address deinterleaving of patterns in time series, in particular, radar signals. We link signal clustering problem to min-cost flow as an equivalent problem once the proper costs exist. We formulate a bi-level optimization problem involving min-cost flow as a sub-problem to learn such costs from the supervised training data. We then approximate the lower level optimization problem by self-attention based neural networks and provide a trainable framework that clu...
A temporal neural network model for constructing connectionist expert system knowledge bases Alpaslan, Ferda Nur (Elsevier BV, 1996-04-01) This paper introduces a temporal feedforward neural network model that can be applied to a number of neural network application areas, including connectionist expert systems. The neural network model has a multi-layer structure, i.e. the number of layers is not limited. Also, the model has the flexibility of defining output nodes in any layer. This is especially important for connectionist expert system applications.
A modified algorithm for peer-to-peer security Akleylek, Sedat; Emmungil, Levent; NURİYEV, URFAT (2007-01-01) In this paper we present the steganographic approach to peer-to-peer systems with a modified algorithm. This gives the user a very high level of protection against being compelled to disclose its contents. Even the realization of the quantum computer cannot solve NP-hard problem in a polynomial time, a modified algorithm with steganographic use depending on Knapsack problem may make peer-to-peer systems secure.

Citation Formats

E. Aydın Göl and C. Belta, “A formal methods approach to pattern synthesis in reaction diffusion systems,” 2015, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/33259.