Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Data Structures
Date
2010
Author
Çiçekli, Fehime Nihan
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
298
views
0
downloads
Cite This
Classification of data structures, space and time considerations. Linked lists,stacks and queues, tree structures, graphs. Array and pointer based implementations. Recursive applications.
URI
https://ocw.metu.edu.tr/course/view.php?id=90
https://hdl.handle.net/11511/36987
Collections
Department of Computer Engineering, Course Material
Suggestions
OpenMETU
Core
APPROXIMATION OF BOUNDS ON MIXED-LEVEL ORTHOGONAL ARRAYS
Sezer, Ali Devin; Özbudak, Ferruh (2011-06-01)
Mixed-level orthogonal arrays are basic structures in experimental design. We develop three algorithms that compute Rao- and Gilbert-Varshamov-type bounds for mixed-level orthogonal arrays. The computational complexity of the terms involved in the original combinatorial representations of these bounds can grow fast as the parameters of the arrays increase and this justifies the construction of these algorithms. The first is a recursive algorithm that computes the bounds exactly, the second is based on an as...
Temporal logic inference for classification and prediction from data
Kong, Zhaodan; Jones, Austin; Medina, Ayala Ana; Aydın Göl, Ebru; Belta, Calin (2014-04-15)
This paper presents an inference algorithm that can discover temporal logic properties of a system from data. Our algorithm operates on finite time system trajectories that are labeled according to whether or not they demonstrate some desirable system properties (e.g. "the car successfully stops before hitting an obstruction"). A temporal logic formula that can discriminate between the desirable behaviors and the undesirable ones is constructed. The formulae also indicate possible causes for each set of beh...
Parallel solution of soil-structure interaction problems on pc clusters
Bahçecioğlu, Tunç; Çetin, Kemal Önder; Department of Civil Engineering (2011)
Numerical assessment of soil structure interaction problems require heavy computational efforts because of the dynamic and iterative (nonlinear) nature of the problems. Furthermore, modeling soil-structure interaction may require finer meshes in order to get reliable results. Latest computing technologies must be utilized to achieve results in reasonable run times. This study focuses on development and implantation of a parallel dynamic finite element analysis method for numerical solution of soil-structure i...
Domain-Structured Chaos in a Hopfield Neural Network
Akhmet, Marat (World Scientific Pub Co Pte Lt, 2019-12-30)
In this paper, we provide a new method for constructing chaotic Hopfield neural networks. Our approach is based on structuring the domain to form a special set through the discrete evolution of the network state variables. In the chaotic regime, the formed set is invariant under the system governing the dynamics of the neural network. The approach can be viewed as an extension of the unimodality technique for one-dimensional map, thereby generating chaos from higher-dimensional systems. We show that the dis...
Domain Structured Dynamics: Unpredictability, chaos, randomness, fractals, differential equations and neural networks
Akhmet, Marat (Institute of Physics Publishing (IOP), 2021-03-01)
Domain structured dynamics introduces a way for analysis of chaos in fractals, neural networks and random processes. It starts with newly invented abstract similarity sets and maps, which are in the basis of the abstract similarity dynamics. Then a labeling procedure is designed to determine the domain structured dynamics. The results follow the Pythagorean doctrine, considering finite number of indices for the labeling, with potential to become universal in future. The immediate power of the approach for f...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
F. N. Çiçekli, “Data Structures,” 00, 2010, Accessed: 00, 2020. [Online]. Available: https://ocw.metu.edu.tr/course/view.php?id=90.