10708 Graphical Models: Homework 1
Due October 1st, beginning of class
September 29, 2008
Instructions: There are five questions on this assignment. The last question involves coding, which should be done in MATLAB. Do not attach your code to the writeup.
Dai Hoc Quc Gia TpHCM BAP AN DE KIEM TRA CUOI HOC KY 2015/2016
Truong Dai Hoc Bach Khoa MON: MACH DIEN TU
Khoa Diem Din T0 Ngay: 21/12/2015
BC) Mon Vin Thong Thoi gian 1am bai: 105 phlit
OoOoo Sinh vin khng duo/c php sir dung tzli lieu
Cu 1 (2.5 dim); Xet
DAI HQC QUc GIA TP. HCM KY 1111 KllflM TRA (31101 1100 KY
TRUONG DAI HQC EACH KHOA MON: MACH 11113311 T111 1 _ 405023
KHOA DIEN DIEN TU Nghy Thi: 09/00/2014
BC) MON VIEN THONG T1101 gim: 105 1311111 (071115  001100)
00000 811111 Vin KHONG D1101: Php S' D
Biu din tn hiu
1. Tm tt l thuyt
Dy tun hon l dy tha mn iu kin: x(n) = x(n + kN), vi N l chu k v k l
mt s nguyn bt k.
Nng lng ca mt dy x(n) c xc nh theo cng thc:

Nng lng trong khong xc nh t K n K c xc nh theo cng thc:



Cng xut trung bnh ca mt dy k
Trng i Hc Bch Khoa Tp.H Ch Minh
Khoa Khoa Hc v K Thut My Tnh
THI MN CNG NGH PHN MN
HC K 2 (2014  2015)
Thi gian : 90 pht
c php s dng ti liu
1
Cu 1 (c 3 mc)
Trong khi thit k chi tit mt h thng ng k mn hc, cc k s phn mn
tho lun v thng nht nh sau
 Mt lp i
1. Bin i Z ngc
1.1. Tm x(n) c bin i Z nh sau :
2
() = 2
1.5 + 0.5
Gi :
xc nh x(n), phng php n gin nht l phn r X(z) thnh cc dng quen thuc
tin hnh tra bng bin i Z. T , xc nh x(n).
Phn tch X(z) : c th bc ny s phn tch i lng X(z)/z
()
=
2
1.5 + 0.5
=
( 1)
N TP CUI K MN PHNG PHP TNH
Bi ging in t
TS. L Xun i
Trng i hc Bch Khoa TP HCM
Khoa Khoa hc ng dng, b mn Ton ng dng
TP. HCM 2013.
TS. L Xun i (BK TPHCM)
N TP CUI K MN PHNG PHP TNH
TP. HCM 2013.
1/1
Cho M = 3.3. ShiftSTOM
Cu 1. Cho phng trnh e x + 2x 2 8
N TP CUI K
PHNG PHP TNH
I. S gn ng v sai s:
Sai s tng i: a
Sai s tuyt i: a = a .  a 
S ch s ng tin: k log ( 2 a )
Sai s lun lun lm trn ln (bt k qu bn hay khng).
y f ( x1 , x2 ,., xn )
n
y
i 1
f
x1 , x2 ,., xn xi
xi
II. Phng php trnh phi tuyn:
1. Sai
Chapter 6:
Acquisitions and takeovers
This chapter is based on:
 Chapter 26: Acquisitions and takeovers of Corporate Finance by Damodaran
To Thi Thu and A. Schmitt, 2009, Key success factors and obstacles of M&A in
Vietnam, 2009, International Vision, 1
CHAPTER 1: Bond markets,
analysis and strategies
A bond is a debt instrument requiring the issuer (also called
the debtor or borrower) to repay to the lender/investor the
amount borrowed plus interest over a specified period of time
Section 1. Pricing o
Chapter 2
Introduction to derivatives
Based on Options, Futures, and Other Derivatives,John C. Hull
1
The Ho Chi Minh Stock Exchange
plans to implement derivatives
market before 2015.
Nguyen Thi Viet Ha,
Head of R&D,Hochiminh Stock Exchange
Based on Opti
Bond Price
If C = 0 then
Bond Price between coupon payments (has f)
Number of days until next coupon payment
If C = 0 then
Macaulay Duration =
If C = 0 then Macaulay Duration = n  1 + f
Modified Duration = (Macaulay Duration)
Return during the holding pe
Centre FrancoVietnamien de Formation la Gestion CFVG
MBA 20
FINANCIAL MARKETS Andr Schmitt
Financial markets group assignments
Guidelines
You work on one assignment in groups of 4 students formed randomly by CFVG. The
assignment is chosen by the teacher.
1
RISK MANAGEMENT: PROFILING AND HEDGING
To manage risk, you first have to understand the risks that you are exposed to.
This process of developing a risk profile thus requires an examination of both the
immediate risks from competition and product market
FINANCIAL MARKETS
Introduction
Andr SCHMITT
1
What have you learnt in corporate finance?
LESSON 1: THE 4 DRIVERS OF FINANCIAL PRICES
1.
2.
3.
4.
Time value of money
Risk
Market efficiency
Arbitrage
2
Lesson 2: Main principles in corporate finance
1. Inves
Key Success factors and obstacles of M&A in Vietnam
By To Thi Thu, Grant Thornton and Andr Schmitt, CFVG
Summary: The aim of this paper is to establish the key success factors of M&A in Vietnam
and the main obstacles remaining in the aftermath of the fina
CHNG 5
BIN NGU NHIN V PHN PHI XC SUT
(Random Variables and Probability Distributons)
5. NH NGHA BIN NGU NHIN (Random Variable)
5.1.1. nh ngha
Bin ngu nhin l nhng bin m gi tr ca n c xc nh mt cch ngu nhin.
V mt ton hc, nu mi bin c s ng A thuc tp hp bin c no
Chng 6
LY MU V PHN PHI MU
(Sampling and Sampling Distribution)
6.1. LY MU T TP HP CHNH (Sampling from a Population)
6.1.1. Tp hp chnh (Population)
Tp hp chnh l tp hp tt c cc i tng m ta quan tm nghin cu trong mt vn
no . S phn t ca tp hp chnh c k hiu l N.
A 9 5% confidence interval for b1 is determined to be (15,30). Interpret the meaning of this interval.
A 95% confidence interval for the mean can be interpreted to mean which of the following?
A candy bar manufacturer is interested in estimating how sales
Most analysts forcus on the cost of tuition as the way to measure the cost of college education.
The chancellor of a ma
all firstyear Drummand University Students
Q1: Anwser: D
Q2: Anwser: C
Q3: Anwser: A
Q4: Anwser: D
Q5: Anwser: B
Q6: Anwser: C
Q7: Anw
Business decisions may be made by interpreting facts derived from statistical analysis
Managers study the number of days per month over the last year that employees in the payroll
By what degree might a variable without a clear operational definition affe
PART 1: DATA COLLECTION, PRESENTING DATA IN TABLES AND CHARTS
I.
DEFINTIONS
Statistics
Population: is the collection of all items
of interest or under investigation (N)
Values calculated using population data
are called parameters
Descriptive statistics:
Cn bn UML: S lp
Gii thiu v cc s cu trc trong UML 2
Donald Bell
Chuyn gia IT
IBM
26 03 2010
T Edge Rational: l v d quan trng nht v kiu s cu trc mi trong UML 2, s lp c
th c cc nh phn tch, cc nh to m hnh nghip v, cc nh pht trin phn mm v
cc nh kim th s dng tr