MATLAB Demystified phần 6 pps
MATLAB Demystified phần 6 pps
...
Figure 6- 4 A plot of
f (x) = x
3
– 3x
2
+ 3x
0 0.2 0.4 0 .6 0.8 1 1.2 1.4 1 .6 1.8 2
0
0.2
0.4
0 .6
0.8
1
1.2
1.4
1 .6
1.8
2
x
x
3
− 3x
2
+ 3x
164
MATLAB Demystifi ed
SOLUTION 6- 8
Using MATLAB ... Figure 6- 6.
Figure 6- 6 A plot of f (x) = x
4
– 2x
3
identifying the local minimum found in Example 6- 6
−2 −1.5 −1 −0.5
0 0.5 1 1.5 2 2.5 3
0
5
10
15
20
25
30
x
x
4...
MATLAB Demystified phần 1 pps
... algebra on paper, MATLAB doesn’t know what to do with it. On the other
hand, MATLAB is completely happy if you assign the value 90 – 6 to the variable
x by writing
x = 90 – 6
16
MATLAB Demystifi ... 1.4918 1 .64 87
1.8221 2.0138 2.2255 2.45 96
Column 11
2.7183
Or we could have y = x
2
:
>> y = x^2
y =
Columns 1 through 10
0 0.0100 0.0400 0.0900 0. 160 0 0.2500
0. 360...
MATLAB Demystified phần 5 pps
... 5 -6.
−10 −8 6 −4 −2
0 2 4 6 8 10
0
1000
2000
3000
4000
5000
60 00
7000
8000
9000
10000
x
x
4
− 5x
3
+ 4x
2
− 5x + 6
Figure 5 -6 Plot of the function x
4
− 5x
3
+ 4x
2
− 5x + 6
1 26
MATLAB ... terms:
> s = taylor(sin(x),20)
s =
x–1 /6* x^3+1/120*x^5–1/5040*x^7+1/ 362 880*x^9–1/
399 168 00*x^11+1 /62 27020800*x^13–1/130 767 4 368 000*x^15+1/
35 568 74280 960 00*x^17–1/12...
Accounting Demystified phần 6 pdf
... be
2
/12 or
1
/6. Annual
depreciation for a full year would be $10,000 (the cost of
$60 ,000 divided by 6 years). Prorating the $10,000 gives the
final year’s depreciation as $1 ,66 7 (computed by ... taking
$10,000 and multiplying by
1
/6) . The entry to record this partial
year’s depreciation is:
XX/XX/XX Depreciation expense 1 ,66 7
Accumulated depreciation—Equipment 1 ,66 7
To record...
Accounting Demystified phần 7 pps
... 23,000
Office supplies 15,000
Office expense 12,000
Total expenses $2, 462 ,500
Net income $61 ,500
10288$ CH17 08-29-03 08:31: 36 PS
110
Accounting Demystified
FIGURE 17-3
Jeffry Haber Company
Income Statement
For ... 08:31:39 PS
112
Accounting Demystified
FIGURE 17 -6
Jeffry Haber Company
Income Statement
For the Year Ended December 31, 2002
Sales $2,500,000
Cost of goods sold 1 ,65 0,00...
MATLAB Demystified phần 2 pptx
... inverse must exist. MATLAB spits it out for us:
>> T = inv(S)
T =
–0.9259 0.4815 0.4815 0.1111
–0 .62 96 0.1574 0 .65 74 0.05 56
–0.59 26 0.1481 0.1481 0.1111
0 .66 67 –0. 166 7 –0. 166 7 0
CHAPTER 2 ... =
64 2 3 61 60 6 7 57
9 55 54 12 13 51 50 16
17 47 46 20 21 43 42 24
40 26 27 37 36 30 31 33
32 34 35 29 28 38 39 25
41 23 22 44 45 19 18 48
49 15 14 52 53 11 10...
MATLAB Demystified phần 3 ppt
... next
example, we will plot y = tanh(x) over the range 6 ≤ x ≤ 6 with a grid display. First
we define our interval:
>> x = [ 6: 0.01 :6] ;
Next, we define the function:
>> y = tanh(x);
The ...
your first function, call subplot, and tell MATLAB where to place it,
then call plot to draw the curve. Then repeat for the next function
66
MATLAB Demystifi ed
This squares eac...
MATLAB Demystified phần 4 pptx
... 36
1 06
MATLAB Demystifi ed
First let’s generate an array of probabilities:
>> p = y/N
p =
Columns 1 through 10
0.0278 0.05 56 0.0278 0. 166 7 0.1111 0.1944
0.05 56 0.0278 0.0833 0.05 56
Columns ... 4 2 9]
A =
104
MATLAB Demystifi ed
1 2 3
4 4 2
4 2 9
>> mean(A)
ans =
3.0000 2 .66 67 4 .66 67
But this simple built-in function won’t work for when the data is weigh...
MATLAB Demystified phần 7 docx
... ft/s is found to be:
t 123 4 5 6 7 8 9 10
v(t) 65 95 110 150 170 210 240 260 265 272
Find the total distance covered by the sled.
204
MATLAB Demystifi ed
SOLUTION 8 -6
The curve is shown in Figure ... −0.2
0 0.2 0.4 0 .6
−0.4
−0.2
0
0.2
0.4
0 .6
0.8
1
x
y
Figure 7-8 The phase portrait for the system solved in Example 7-2
2 16
MATLAB Demystifi ed
So the sled has traveled 166 8.50...
MATLAB Demystified phần 8 docx
... command:
>> w = m*handicap + b
w =
3. 861 6 3.9399 4.0182 4.0 965 4.1748 4.2532
4.3315 4.4098 4.4881 4. 566 4
248
MATLAB Demystifi ed
The data together with the line MATLAB has come up with to fit it ... then:
r
A
S
2
1=−
Average
4 .6
4.4
4.2
4
3.8
3 .6
6 8 10 12 14 16 18 20 22 24
Handicap
Figure 10-1 A plot of the data along with the least squares
fit generated in Example 1...