- published: 31 Mar 2012
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A concept is an abstraction or generalization from experience or the result of a transformation of existing ideas. The concept is instantiated (reified) by all of its actual or potential instances, whether these are things in the real world or other ideas. Concepts are treated in many if not most disciplines both explicitly, such as in psychology, philosophy, etc., and implicitly, such as in mathematics, physics, etc. In informal use the word concept often just means any idea, but formally it involves the abstraction component.
In metaphysics, and especially ontology, a concept is a fundamental category of existence. In contemporary philosophy, there are at least three prevailing ways to understand what a concept is:
In mathematics and computer science, an algorithm (^{i}/ˈælɡərɪðəm/ AL-gə-ri-dhəm) is a self-contained step-by-step set of operations to be performed. Algorithms exist that perform calculation, data processing, and automated reasoning.
The words 'algorithm' and 'algorism' come from the name al-Khwārizmī. Al-Khwārizmī (Persian: خوارزمي, c. 780-850) was a Persian mathematician, astronomer, geographer, and scholar.
An algorithm is an effective method that can be expressed within a finite amount of space and time and in a well-defined formal language for calculating a function. Starting from an initial state and initial input (perhaps empty), the instructions describe a computation that, when executed, proceeds through a finite number of well-defined successive states, eventually producing "output" and terminating at a final ending state. The transition from one state to the next is not necessarily deterministic; some algorithms, known as randomized algorithms, incorporate random input.
In computer science, the time complexity of an algorithm quantifies the amount of time taken by an algorithm to run as a function of the length of the string representing the input. The time complexity of an algorithm is commonly expressed using big O notation, which excludes coefficients and lower order terms. When expressed this way, the time complexity is said to be described asymptotically, i.e., as the input size goes to infinity. For example, if the time required by an algorithm on all inputs of size n is at most 5n^{3} + 3n for any n (bigger than some n_{0}), the asymptotic time complexity is O(n^{3}).
Time complexity is commonly estimated by counting the number of elementary operations performed by the algorithm, where an elementary operation takes a fixed amount of time to perform. Thus the amount of time taken and the number of elementary operations performed by the algorithm differ by at most a constant factor.
Since an algorithm's performance time may vary with different inputs of the same size, one commonly uses the worst-case time complexity of an algorithm, denoted as T(n), which is defined as the maximum amount of time taken on any input of size n. Less common, and usually specified explicitly, is the measure of average-case complexity. Time complexities are classified by the nature of the function T(n). For instance, an algorithm with T(n) = O(n) is called a linear time algorithm, and an algorithm with T(n) = O(M^{n}) and M^{n}= O(T(n)) for some M ≥ n > 1 is said to be an exponential time algorithm.
Level 2 or Level II may refer to:
Pseudocode is an informal high-level description of the operating principle of a computer program or other algorithm.
It uses the structural conventions of a programming language, but is intended for human reading rather than machine reading. Pseudocode typically omits details that are essential for machine understanding of the algorithm, such as variable declarations, system-specific code and some subroutines. The programming language is augmented with natural language description details, where convenient, or with compact mathematical notation. The purpose of using pseudocode is that it is easier for people to understand than conventional programming language code, and that it is an efficient and environment-independent description of the key principles of an algorithm. It is commonly used in textbooks and scientific publications that are documenting various algorithms, and also in planning of computer program development, for sketching out the structure of the program before the actual coding takes place.
Concepts of Algorithm, Flow Chart & C Programming by Prof. Wongmulin | Dept. of Computer Science Garden City College-Bangalore
This module explains the concept of Algorithm with the help of real life example. It also describes the concept of Generalized algorithm and its advantages. At Cognifront, we are creating revolution in Engineering Education.. Our Software Products are crafted with latest technology. We embarked on this grand vision to help transform technical education all across this beautiful planet. Become a part of it..
Algorithm using Flowchart and Pseudo code Level 2 Important Programming Concepts By: Yusuf Shakeel 0:05 Level 2 0:10 important Programming Concepts 0:16 Semicolon 0:36 Comment 1:05 Data item - Numeric Character String Boolean 1:55 Variable 2:05 Example of variables 2:50 Constant 3:17 Assignment Operator = 3:37 Mathematical Operators + - * / 4:04 Increment Operator ++ 4:26 Decrement Operator -- 4:52 Post Increment 5:31 Pre Increment 6:10 Post Decrement 6:41 Pre Decrement 7:10 Modulus Operator % 7:39 Logical Operator AND OR NOT 8:02 Logical AND Operator && 8:27 Logical OR Operator || 8:44 Logical NOT Operator ! 9:10 Relational Operator 9:34 Modulus Operation Exercise 9:37 Find whether a given number is ODD or EVEN 10:02 Logical Operator Exercise 10:08 Print "Valid" if a is 10 and b is 20 el...
Asymptotic Time complexity, Running Time analysis of Algorithms-Asymptotic Time complexity-Part 2-GATE exam preparation videos for computer science, asymptotic analysis of algorithms, algorithm efficiency analysis, how to compute the running time of an algorithm, complexity of algorithm, finding running time of an algorithm, notes on running time of algorithms, analysing algorithm, growth rate algorithms find maximum element in array Time complexity Analysis of iterative programs Time complexity of a triple-nested loop time complexity of algorithms for loop time complexity examples time complexity of while loop for (int i = 1; i less than equal to n; ++i) for (int j = i; j less than equal to n; ++j) for (int k = j; k less than equal to n; ++k) // statement The s...
This Video demonstrates the concept of Round Robin (RR) and also problem solving techniques related to RR.
Welcome to part 1 of a new series of videos focused on Evolutionary Computing, and more specifically, Genetic Algorithms. In this tutorial, I introduce the concept of a genetic algorithm, how it can be used to approach "search" problems and how it relates to brute force algorithms. Support this channel on Patreon: https://www.patreon.com/codingrainbow Send me your questions and coding challenges!: https://github.com/CodingRainbow/Rainbow-Topics Contact: https://twitter.com/shiffman Links discussed in this video: The Nature of Code: http://natureofcode.com/ BoxCar2D: http://boxcar2d.com/ Source Code for the Video Lessons: https://github.com/CodingRainbow/Rainbow-Code p5.js: https://p5js.org/ Processing: https://processing.org For More Genetic Algorithm videos: https://www.youtube.com...
Introduction, to, Algorithms, Analyzing, DAA, gate, iit, lectures, tutorial, in hindi, Introduction to fundamental techniques for designing and analyzing algorithms, including asymptotic analysis; divide-and-conquer algorithms
It covers the concepts of Filling a polygon through Scan Lines. For more details about the algorithm visit: http://www.unacademy.in/2012/01/scan-line-polygon-fill-algorithm.html Follow us on Facebook http://www.facebook.com/unacademy
View full lesson: http://ed.ted.com/lessons/your-brain-can-solve-algorithms-david-j-malan An algorithm is a mathematical method of solving problems both big and small. Though computers run algorithms constantly, humans can also solve problems with algorithms. David J. Malan explains how algorithms can be used in seemingly simple situations and also complex ones. Lesson by David J. Malan, animation by enjoyanimation.
Concepts of Algorithm, Flow Chart & C Programming
concept of Randomized algorithms
Concepts of Algorithm, Flow Chart & C Programming by Prof. Wongmulin | Dept. of Computer Science Garden City College-Bangalore
A video on the concept of KMP pattern matching algorithm.
Video 16 - "Cryptography Algorithms and Protocols" - This second nugget of the Cryptography domain lays out hashing concepts and algorithms like MD5 and SHA. Basic algorithms and encryption concepts are explored including: DES, 3DES, RSA, PGP, Elliptic curve (ECC), AES/AES256, One time pad, SSL/TLS, S/MIME, and PPTP/L2TP.
Topics covered: Concept learning, Find-S algorithm (Audio not working)
Video 26 - UPDATE regarding Cryptography Algorithms and Protocols, plus Cryptography Domain. Cryptography domain lays out hashing concepts and algorithms like MD5 and SHA. Basic algorithms and encryption concepts are explored including: DES, 3DES, RSA, PGP, Elliptic curve (ECC), AES/AES256, One time pad, SSL/TLS, S/MIME, and PPTP/L2TP. Cryptography domain lays out the core concepts of a Public Key Infrastructure (PKI).
http://CppCon.org — Presentation Slides, PDFs, Source Code and other presenter materials are available at: https://github.com/cppcon/cppcon2016 — Algorithms and the Concepts that enable them (Range and Iterator) are designed to work over values distributed in space (VDiS). The algorithms in std and the rangev3 proposal and the parallel algorithm are all focused on efficiently utilizing every resource assigned to them to process values distributed in space. Whenever values are distributed in space, these are the tools to use. Values distributed in time (VDiT) require different Concepts and Algorithms. This talk will explore some of these Algorithms and the requirements that they impose on the Concepts. The result is a library that composes algorithms the same way that the rangev3 proposal...
From this lecture, you can learn how to use ga algorithm provided from MATLAB 2012a or later versions without understanding the concept of genetic algorithm.