+ log (n/2) +...+ log (n/2) log (n!) (n/2) log (n/2) ‚ n/2>0 for sufficiently large n log (n!) = (n log n) So log (n!) = Θ (nlog n) Q3) Design an algorithm that uses comparisons to select the largest and the second largest of n elements. Find the time complexity of your algorithm (expressed using the big-O notation). String MaxAndSecond(int a[]‚int n) { int max =0‚ second =0; max = a[0]; for (i = 1; i < n; i++) { if (a[i] >= max)
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9 15 Draw a timeline for each of the following scheduling algorithm. (It may be helpful to first compute to first compute a start and finish time for each job). a. FCFS b. SJN c. SRT d. Round Robin (using a time quantum of 5‚ ignore context switching and natural wait) 6. Using the same information given for question 5‚ complete the chart by computing waiting time and turnaround time for each of the following scheduling algorithms (Ignoring context switching overhead). a. FCFS b. SJN c
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Dynamic Signal Analyzer for dSPACE K. A. Lilienkamp‚ and D. L. Trumper Precision Motion Control Lab‚ MIT‚ Rm 35-030‚ 77 Mass. Ave‚ Cambridge‚ MA 02139 We have developed MATLAB software and a Simulink subsystem block which work in tandem to extract the transfer function (amplitude and phase) of a system using ‘swept sine’ excitation. The resulting dynamic signal analyzer provides a convenient tool for obtaining empirical Bode plots of system and controller dynamics within the dSPACE environment.
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types of algorithms and this is the reasons behind the success of this applications. Algorithms is a formula or set of steps for solving a particular problem. A set of rules must be unambiguous and have a clear stopping point. Algorithm can be expressed in any language‚ from natural languages like English or French to programming languages like FORTRAN. Most programs‚ with the exception of some artificial intelligence applications‚ consist of algorithms. Inventing elegant algorithms that are simple
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Processing Letters 75 (2000) 243–246 A fast algorithm for computing large Fibonacci numbers Daisuke Takahashi Department of Information and Computer Sciences‚ Saitama University‚ 255 Shimo-Okubo‚ Urawa-shi‚ Saitama 338-8570‚ Japan Received 13 March 2000; received in revised form 19 June 2000 Communicated by K. Iwama Abstract We present a fast algorithm for computing large Fibonacci numbers. It is known that the product of Lucas numbers algorithm uses the fewest bit operations to compute the
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Purchase TCO #2– Given a simple business problem‚ design a solution algorithm that uses arithmetic expressions and built-in functions. Assignment: Your goal is to solve the following simple programming exercise. You have been contracted by a local restaurant to design an algorithm determining the total meal charges. The algorithm should ask the user for the total food purchase and the tip percent. Then‚ the algorithm will calculate the amount of a tip‚ a 7% sales tax‚ and the total meal
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3.5 RADIX-2 BOOTH ALGORITHM As mentioned earlier‚ A.D Booth proposed a encoding technique for the reduction of partial products for designing a low power and an efficient multiplier. Booth algorithm provides a process for multiplying binary integers in signed –2‘s complement form. For Example‚ DECIMAL BINARY -4 X 2 1100 X 0010 This algorithm is also known as radix-2 booth recording algorithm. The multiplier is recorded as Zi for every ith bit Yi with reference to Yi-1. This is based on the fact
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Recognition Algorithms Dhiresh R. Surajpal and Tshilidzi Marwala Abstract— This paper explores a comparative study of both the linear and kernel implementations of three of the most popular Appearance-based Face Recognition projection classes‚ these being the methodologies of Principal Component Analysis (PCA)‚ Linear Discriminant Analysis (LDA) and Independent Component Analysis (ICA). The experimental procedure provides a platform of equal working conditions and examines the ten algorithms in the
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Structures‚ Algorithm Analysis: Table of Contents 页码，1/1 Data Structures and Algorithm Analysis in C by Mark Allen Weiss PREFACE CHAPTER 1: INTRODUCTION CHAPTER 2: ALGORITHM ANALYSIS CHAPTER 3: LISTS‚ STACKS‚ AND QUEUES CHAPTER 4: TREES CHAPTER 5: HASHING CHAPTER 6: PRIORITY QUEUES (HEAPS) CHAPTER 7: SORTING CHAPTER 8: THE DISJOINT SET ADT CHAPTER 9: GRAPH ALGORITHMS CHAPTER 10: ALGORITHM DESIGN TECHNIQUES CHAPTER 11: AMORTIZED ANALYSIS mk:@MSITStore:K:\Data.Structures.and.Algorithm.Analysis
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HYBRID FUZZY RULE BASED CLASSIFICATION ALGORITHM Introduction 1.1 Purpose The purpose of this document is to design a strategy for hybrid fuzzy rule base classification algorithm using the weka tool. This document outlines the functional requirements for hybrid fuzzy rule based classification algorithm. This document discusses the project’s goals and parameters‚ while giving descriptions about the potential design issues. The requirements are specified according to the finished product. 1.2
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