Booth In Action
• For each multiplier bit, also examine bit to its right
• • • • 00: 10: 11: 01: middle of a run of 0s, do nothing beginning of a run of 1s, subtract multiplicand middle of a run of 1s, do nothing end of a run of 1s, add multiplicand

Booth in Summary
• Performance/efficiency
+ Good for sequences of 3 or more 1s • Replaces 3 (or more) adds with 1 add and 1 subtract • Doesn’t matter for sequences of 2 1s • Replaces 2 adds with 1 add and 1 subtract (add = subtract) – Actually bad for singleton 1s • Replaces 1 add with 1 add and 1 subtract

• Bottom line
• Worst case multiplier (101010) requires N/2 adds + N/2 subs • What is the worst case multiplier for straight multiplication? • How is this better than normal multiplication?

...Yapala
VHDL IMPLEMENTAION USING SPIKE SORTING ALGORITHM
A THESIS SUBMITTED IN PARTIAL FULFILMENT OF THE DEGREE OF MASTER OF SCIENCE IN MICRO ELECTRONICS
VHDLIMPLEMENTATIONUSING SPIKE SORTING ALGORITHM
A Thesis submitted to Newcastle University for the degree of MSc Micro Electronics
2011
Supervisor: Dr Graeme Chester
Student Name: Ramya Yapala
Student Number: 109230832
SCHOOL OF ELECTRICAL, ELECTRONIC AND COMPUTER ENGINEERING
NEWCASTLE UNIVERSITY
SCHOOL OF ELECTRICAL, ELECTRONIC AND COMPUTER ENGINEERING
I, <Ramya Yapala>, confirm that this report and the work presented in it are my own achievement.
I have read and understand the penalties associated with plagiarism.
Signed: ……………………………………………………………………………………….
Date: ………………………………………………………………………………………….
Acknowledgment
My deepest indebted goes first to my supervisor Doctor Graeme Chester. He instructed me a lot in the past one year. Without his patient and illuminating instruction, I could not finish this project. His guidance and encouragement helps me overcome all the problems of the investigation of this project.
I would also wish to thank PhD student Reza Rafiee and my friends who have helped in successfully finishing the project.
Most importantly, I owe special gratitude to my beloved families for their loving considerations and great confidence in me.
Abstract
This project...

...MAMTHA PRAJAPATI
Email: mamthaprajapati@gmail.com
Phone no: +91 7597872069
[pic]
CAREER OBJECTIVE
“To constantly update my technical skills and use them to the best, in pursuit of professional and personal growth”.
EDUCATIONAL QUALIFICATIONS
Pursuing M.Tech in VLSI Design, MITS Lakshmangarh, Rajasthan
|Examination |Institute |University/ |Percentage of Marks Obtained |
| | |Board | |
|B.Tech (Electronics and |Vignan’s Institute Of |Jawaharlal Nehru | |
|Communication Engineering) |Information Technology |Technological University |75.63% |
|(2006-10) | | | |
|Intermediate |Chaitanya Junior College, |Board of Intermediate | |
|(2004-06) |Vizag |Education |92.2% |
|Std X | Ramakrishna public School, |Board of Secondary | |
|(2003-04) |Vizag...

...
Experiment Name:Insertion sort Algorithm
Objective:To learn about Insertion sort algorithm,know how it works and use it in real life.
Application: Suppose there exists a function called Insert designed to insert a value into a sorted sequence at the beginning of an array. It operates by beginning at the end of the sequence and shifting each element one place to the right until a suitable position is found for the new element. The function has the side effect of overwriting the value stored immediately after the sorted sequence in the array.To perform an insertion sort, begin at the left-most element of the array and invoke Insert to insert each element encountered into its correct position. The ordered sequence into which the element is inserted is stored at the beginning of the array in the set of indices already examined. Each insertion overwrites a single value: the value being inserted.
Pseudocode:
// The values in A[i] are checked in-order, starting at the second one
for i ← 1 to i ← length(A)
{
// at the start of the iteration, A[0..i-1] are in sorted order
// this iteration will insert A[i] into that sorted order
// save A[i], the value that will be inserted into the array on this iteration
valueToInsert ← A[i]
// now mark position i as the hole; A[i]=A[holePos] is now empty
holePos ← i
// keep moving the hole down until the valueToInsert is larger than
// what's just below the hole or the...

...Question 1
In what follows we consider two simple algorithms for the Knapsack problem. We assume without
loss of generality, that for every object i we have si B (or else we can remove the object from the
set of objects).
Item A. Consider the following greedy algorithm for the knapsack problem: For each object i,
compute the “profit-to-size” ratio ri = pi/si. We order the objects according to ri, from big to small,
and then go over the objects in this order and add an object if it doesn’t violate the size constraint
(that is, the total size of the selected objects is at most B). Show that the approximation factor this
algorithm gives may grow (at least) linearly with B (so that in particular it is not any fixed constant
or even a function of the number of objects).
Item B. We modify the algorithm in the previous item as follows. We still order the objects according
to the ri’s. We then find the minimal k such that the total size of the first k objects according to this
order exceeds B. The algorithm now compares the total profit of the first k − 1 objects to the profit
of object k and takes the better of the two. Show that this algorithm gives an approximation factor
of 2.
Question 2
As mentioned in class, there is a more “natural” pseudo-polynomial algorithm for solving the Knapsack
problem using a dynamic programming approach. Specifically,...

...510.6401 Design and Analysis of Algorithms
January 21, 2008
Problem Set 1
Due: February 4, 2008. 1. In the bin packing problem, the input consists of a sequence of items I = {1, . . . , n} where each item i has a size, which is a real number 0 ≤ ai ≤ 1. The goal is to “pack” the items in the smallest possible number of bins of unit size. Formally, the items should be partitioned in disjoint subsets (bins), such that the total size in each bin is at most 1. The ﬁrst ﬁt heuristic scans the items one by one, and each item is assigned to the ﬁrst bin that it can ﬁt in. Prove that ﬁrst-ﬁt is a 2-approximation algorithm for bin packing. Hint. Bound from below the number of bins used by an optimal solution; and bound from above the number of bins used by ﬁrst ﬁt, using the observation that nearly all bins are at least half-full. 2. Suppose now that you want to pack as much as possible in a single bin. Formally, the input consists of a set of items I = {1, . . . , n}, where each item i has a size 0 < ai ≤ 1. A solution is a set of items S ⊂ I such that i∈S ai ≤ 1 (i.e., the size of the bag is 1). The value of a solution S is the total size of the items in the solution, i.e., i∈S ai . (a) Describe an optimal solution to the problem. What is the time complexity of your algorithm? (b) Give a polynomial-time algorithm with approximation ratio 2 (i.e., it guarantees that you ﬁll at least half of...

...TK3043 : Analysis and Design of Algorithms
Assignment 3
1. Compute the following sums:
a. ∑
Answer:
=∑
=u–1+1
= (n + 1) – 3 + 1
=n+1–2
=n-2
b. ∑
Answer:
=∑
= [1 + 2] + … + n
=∑
+ (n + 1) – (1 + 2)
=∑
+ (n + 1) – 3
=∑
+n –2
= n(n + 1) + (n - 2)
2
= n2 + n + (n - 2)
2
= n2 + 3n – 4
2
c. ∑
Answer:
∑
=∑
=∑
= n (n+1) (2n + 1) + n (n+1)
6
2
= (n - 1) (n -1 + 1) (2 ( n –1) +1) + (n - 1) (n – 1 + 1)
6
2
= (n - 1) (n) (2n – 2 + 1) + (n – 1) (n)
6
2
2
= (n - n) (2n – 1) + (n – 1) (n)
6
2
= (n3 - n2 - 2n2 + n) + (n2 – n)
6
2
= 2n3 - 3n2 + n + n2 – n
6
2
= 2n3 - 3n2 + n + 3n3 – 3n
6
= 2n3 – 2n
6
= n3 – n
3
2
=n –1
3
2. Consider the following algorithm.
Algorithm Mystery( n)
//Input: A nonnegative integer n
S←0
for i ← 1 to n do
S←S+i*i
return S
a. What does this algorithm compute?
Answer:
2
S(n) = ∑
b. What is its basic operation?
Answer:
Multiplication
c. How many times is the basic operation executed?
Answer:
At least one time
d. What is the efficiency class of this algorithm?
Answer:
C(n) = n (n)
e. Suggest an improvement or a better algorithm altogether and indicate its efficiency
class. If you cannot do it, try to prove that, in fact, it cannot be done.
Answer:
∑
2
= n (n + 1) (2n + 1)
6
3. Consider the following algorithm.
Algorithm Secret(A[0..n − 1])...

...DESIGN AND IMPLEMENTATION OF AN ONLINE STUDENT ADMISSION SYSTEM
(A CASE STUDY OF FEDERAL COLLEGE OF EDUCATION, EHA-AMUFU, ENUGU STATE)
TABLE OF CONTENTS
Title page
Certification
Dedication
Acknowledgement
Abstract
Table of contents
CHAPTER ONE
1.0 INTRODUCTION of “design and implementation of an online students admission system”
1.1 Background of the study
1.2 Statement of the problem
1.3 Purpose of the study
1.4 Significance of the study
1.5 Scope of study
CHAPTER TWO
2.1 LITERATURE REVIEW of “design and implementation of an online students admission system”
2.2 Nature of admission processes
2.3 Problem inherent from admission
2.4 Need for (computerization) an online
CHAPTER THREE
3.1 Description and analysis of the existing system
3.2 Fact finding methods used
3.3 Organizational structure
3.4 Objectives of the existing system
3.5 Input, process and output analysis
3.6 Information flow diagram
CHAPTER FOUR
4.1 Design of the new system
4.2 Output specification and design
4.3 Input specification and design
4.4 Flow Chart/Procedure chart
CHAPTER FIVE
5.1 System Implementation
5.2 Conversion proper
5.3 The parallel approach
CHAPTER SIX
6.1 DOCUMENTATION of “design and implementation of an online students admission system”
6.2 Loading the new program
6.3 Running the program
6.4 Operational...

...Running Head: Implementation Phase of Communication Assets Project (CAP)
Implementation Phase of
Communication Assets Project (CAP)
Sandra Manchor
University of Phoenix
Abstract
This paper discusses the implementation phase of the Communications Assets Project (CAP) Software Configuration Management (SCM). CAP is an interoperable communications inventory software package. The project manager for CAP has asked for an analysis for software configuration management. This paper includes the six major activities: coding, testing, installation, documentation, training and support. This document is a discussion on the transition from the design phase to the implementation phase.
Implementation
"In the implementation phase the system is constructed in a series of iterations where each Use Case and component is coded, tested and integrated into the overall system. This phase is performed iteratively following a time line that accounts for all resources and costs" (SCM, 2004). The following six activities are discussed in the subsequent sections: coding, testing, installation, documentation, training and support. Many benefits are seen when using defined and repeatable processes: clarification of roles and responsibilities, clear definition of procedures, demonstrate standards are being met, the same steps can be used to define other...

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