PDF4PRO ⚡AMP

Modern search engine that looking for books and documents around the web

Example: dental hygienist

Big-Oh notation: few examples - Auckland

the Big-Oh condition cannot hold (the left side of the latter inequality is growing infinitely, so that there is no such constant factor c). Example 3: Prove that running time T(n) = n3 + 20n + 1 is O(n4) Proof: by the Big-Oh definition, T(n) is O(n4) if T(n) ≤ c·n4 for some n ≥ n0 . Let us check this condition: if n3 + 20n + 1 ≤ c·n4 ...

Fullscreen Download

Tags:

  Rattle

Information

Domain:

Source:

Link to this page:

Please notify us if you found a problem with this document:

Spam in document Broken preview Other abuse

Documents from same domain

Introduction to Weka - The University of Auckland

www.cs.auckland.ac.nz

What is Weka? Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code.

  Introduction, Wake, Introduction to weka

Problem Solving with Algorithms and Data Structures

www.cs.auckland.ac.nz

Problem Solving with Algorithms and Data Structures, Release 3.0 Control constructs allow algorithmic steps to be represented in a convenient yet unambiguous way. At a minimum, algorithms require constructs that perform sequential processing, selection for decision-making, and iteration for repetitive control. As long as the language provides these

  Problem, Solving, Logarithmic, Problem solving

When was the first computer invented?

www.cs.auckland.ac.nz

In 1968, Hewlett Packard began marketing the first mass-marketed PC and the first desktop computer, the HP 9100A. The first workstation Although it was never sold, the first workstation is considered to be the Xerox Alto, introduced in 1974. The computer was revolutionary for its time and included a fully functional computer, display, and mouse.

  Hewlett

String Matching Algorithms - Auckland

www.cs.auckland.ac.nz

OutlineString matchingNa veAutomatonRabin-KarpKMPBoyer-MooreOthers 1 String matching algorithms 2 Na ve, or brute-force search 3 Automaton search 4 Rabin-Karp algorithm 5 Knuth-Morris-Pratt algorithm 6 Boyer-Moore algorithm 7 Other string matching algorithms Learning outcomes: Be familiar with string matching algorithms Recommended reading:

  Outcome, Matching, Algorithm, String, String matching algorithms

Image Filtering - Auckland

www.cs.auckland.ac.nz

Median Filtering example The following example shows the application of a median filter to a simple one dimensional signal. A window size of three is used, with one entry immediately preceding and following each entry. ... – It defines a probability distribution for noise or data.

  Data, Example, Filtering, Filtering example

1 Exercises and Solutions - Auckland

www.cs.auckland.ac.nz

4. Assume that each of the expressions below gives the processing time T(n) spent by an algorithm for solving a problem of size n. Select the dominant term(s) having the steepest increase in n and specify the lowest Big-Oh complexity of each algorithm. Expression Dominant term(s) O(...) 5+0.001n3 +0.025n 500n+100n1.5 +50nlog 10 n 0.3n+5n 1.5 +2 ...

  Expression

Gaussian Filtering - Auckland

www.cs.auckland.ac.nz

This means we can normally limit the kernel size to contain only values within three standard deviations of the mean. 5/25/2010 7 ... This is a common first step in edge detectionThis is a common first step in edge detection. The images below have been processed with a …

  Limits, Detection

Python 3 – Turtle graphics - Auckland

www.cs.auckland.ac.nz

Logo and Turtle graphics In 1967, Seymour Papert and Wally Feurzeig created an interpretive programming language called Logo. Papert added commands to Logo so that he could control a turtle robot, which drew shaped on paper, from his computer Turtle graphics is now part of Python Using the Turtle involves instructing the turtle to move on the

  Auckland, Graphics, Turtle, Turtle graphics

Image Filtering - School of Computer Science

www.cs.auckland.ac.nz

5/25/2010 2 Median Filtering example The following example shows the applicati on of a median filter to a simple one dimensional signal. A window size of three is used, wi th one entry immediately preceding and

  Computer, Sciences, Computer science