PIERWSZE ZAJECIA PPS

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>> who
>> a=12.99

a =

   12.9900

>> who

Your variables are:

a  

>> whos
  Name      Size            Bytes  Class     Attributes

  a         1x1                 8  double              

>> A=[ 1 2 3; 4 5 6; 7 8 9] 

A =

     1     2     3
     4     5     6
     7     8     9

>> who

Your variables are:

A  a  

>> whos
  Name      Size            Bytes  Class     Attributes

  A         3x3                72  double              
  a         1x1                 8  double              

>> B=[2 -1 3.5; -0.13 2.2; 3 0.5 34]
Error using vertcat
Dimensions of matrices being concatenated are not consistent.
 
>> B=[2 -1 3.5; -0.13 -0.3 2.2; 3 0.5 34]

B =

    2.0000   -1.0000    3.5000
   -0.1300   -0.3000    2.2000
    3.0000    0.5000   34.0000

>> 
>> whos
  Name      Size            Bytes  Class     Attributes

  A         3x3                72  double              
  B         3x3                72  double              
  a         1x1                 8  double              

>> P=[]

P =

     []

>> whos
  Name      Size            Bytes  Class     Attributes

  A         3x3                72  double              
  B         3x3                72  double              
  P         0x0                 0  double              
  a         1x1                 8  double              

>> Suma = A + B

Suma =

    3.0000    1.0000    6.5000
    3.8700    4.7000    8.2000
   10.0000    8.5000   43.0000

>> Suma A+B ;
Error: "Suma" was previously used as a variable, conflicting with its use here as the name of a function or command.
See "How MATLAB Recognizes Command Syntax" in the MATLAB documentation for details.
 
>> Roz A-B
Undefined function 'Roz' for input arguments of type 'char'.
 
>> Roz= A-B 

Roz =

   -1.0000    3.0000   -0.5000
    4.1300    5.3000    3.8000
    4.0000    7.5000  -25.0000

>> A10=10*A

A10 =

    10    20    30
    40    50    60
    70    80    90

>> AP=5+A

AP =

     6     7     8
     9    10    11
    12    13    14

>> Mnoz=A*B

Mnoz =

   10.7400   -0.1000  109.9000
   25.3500   -2.5000  229.0000
   39.9600   -4.9000  348.1000

>> Dziel = A/B

Dziel =

   -0.4315   -4.5199    0.4251
   -0.4857  -13.2421    1.0833
   -0.5399  -21.9643    1.7415

>> Dziel1 = A*inv(B)

Dziel1 =

   -0.4315   -4.5199    0.4251
   -0.4857  -13.2421    1.0833
   -0.5399  -21.9643    1.7415

>> T=Dziel - Dziel1

T =

   1.0e-14 *

    0.0111   -0.0888   -0.0056
    0.0111         0    0.0222
    0.1221   -0.3553         0

>> Nowa=A.*B

Nowa =

    2.0000   -2.0000   10.5000
   -0.5200   -1.5000   13.2000
   21.0000    4.0000  306.0000

>> // powstajaca macierznowa 
 // powstajaca macierznowa 
 |
Error: Unexpected MATLAB operator.
 
>> // skladniki iloczynu przechowywane sa w tej samej macierzy 
 // skladniki iloczynu przechowywane sa w tej samej macierzy 
 |
Error: Unexpected MATLAB operator.
 
>> pierwszy wyrazA bedzie mial numer 1.1, zawsze peirwszy wiersz druga kolumna 
Undefined function 'pierwszy' for input arguments of type 'char'.
 
>> POT=A.^B

POT =

   1.0e+32 *

    0.0000    0.0000    0.0000
    0.0000    0.0000    0.0000
    0.0000    0.0000    2.7813

>> w podstawie a sa przechowywane wykladniki macierzy B 
Undefined function 'w' for input arguments of type 'char'.
 
>> teraz manipulacja blokami danych 
Undefined function 'teraz' for input arguments of type 'char'.
 
>> a

a =

   12.9900

>> A

A =

     1     2     3
     4     5     6
     7     8     9

>> B

B =

    2.0000   -1.0000    3.5000
   -0.1300   -0.3000    2.2000
    3.0000    0.5000   34.0000

>> chcemy utworzyc macierz 3x6 zeby A dolaczyc z prawej 
Undefined function 'chcemy' for input arguments of type 'char'.
 
>> laczymy teraz tablice
Undefined function 'laczymy' for input arguments of type 'char'.
 
>> AB = [A, B]

AB =

    1.0000    2.0000    3.0000    2.0000   -1.0000    3.5000
    4.0000    5.0000    6.0000   -0.1300   -0.3000    2.2000
    7.0000    8.0000    9.0000    3.0000    0.5000   34.0000

>> utworz nowa macierz w pierwszym wierzu a i drugim wierszu b
Undefined function 'utworz' for input arguments of type 'char'.
 
>> AB1 = [A; B]

AB1 =

    1.0000    2.0000    3.0000
    4.0000    5.0000    6.0000
    7.0000    8.0000    9.0000
    2.0000   -1.0000    3.5000
   -0.1300   -0.3000    2.2000
    3.0000    0.5000   34.0000

>> whos 
  Name        Size            Bytes  Class     Attributes

  A           3x3                72  double              
  A10         3x3                72  double              
  AB          3x6               144  double              
  AB1         6x3               144  double              
  AP          3x3                72  double              
  B           3x3                72  double              
  Dziel       3x3                72  double              
  Dziel1      3x3                72  double              
  Mnoz        3x3                72  double              
  Nowa        3x3                72  double              
  P           0x0                 0  double              
  POT         3x3                72  double              
  Roz         3x3                72  double              
  Suma        3x3                72  double              
  T           3x3                72  double              
  a           1x1                 8  double              

>> ABB = [AB, B, A]

ABB =

    1.0000    2.0000    3.0000    2.0000   -1.0000    3.5000    2.0000   -1.0000    3.5000    1.0000    2.0000    3.0000
    4.0000    5.0000    6.0000   -0.1300   -0.3000    2.2000   -0.1300   -0.3000    2.2000    4.0000    5.0000    6.0000
    7.0000    8.0000    9.0000    3.0000    0.5000   34.0000    3.0000    0.5000   34.0000    7.0000    8.0000    9.0000

>> whos
  Name        Size            Bytes  Class     Attributes

  A           3x3                72  double              
  A10         3x3                72  double              
  AB          3x6               144  double              
  AB1         6x3               144  double              
  ABB         3x12              288  double              
  AP          3x3                72  double              
  B           3x3                72  double              
  Dziel       3x3                72  double              
  Dziel1      3x3                72  double              
  Mnoz        3x3                72  double              
  Nowa        3x3                72  double              
  P           0x0                 0  double              
  POT         3x3                72  double              
  Roz         3x3                72  double              
  Suma        3x3                72  double              
  T           3x3                72  double              
  a           1x1                 8  double              

>> size(ABB)

ans =

     3    12

>> polecenie wyzej to sprawdzenie wielkosci tablicy 
Undefined function 'polecenie' for input arguments of type 'char'.
 
>> AB2= [AB;B,B]

AB2 =

    1.0000    2.0000    3.0000    2.0000   -1.0000    3.5000
    4.0000    5.0000    6.0000   -0.1300   -0.3000    2.2000
    7.0000    8.0000    9.0000    3.0000    0.5000   34.0000
    2.0000   -1.0000    3.5000    2.0000   -1.0000    3.5000
   -0.1300   -0.3000    2.2000   -0.1300   -0.3000    2.2000
    3.0000    0.5000   34.0000    3.0000    0.5000   34.0000

>> AB3 = [A,A;B]
Error using vertcat
Dimensions of matrices being concatenated are not consistent.
 
>> wyzej nie dziala bo niezgodne wymiary 
Undefined function 'wyzej' for input arguments of type 'char'.
 
>> dana=AB(2,3)

dana =

     6

>> 2*6+2

ans =

    14

>> teraz tworzy sie ans czyli answer, nazwa domyslna zmiennej nieprzypisanej zadnej zmiennej 
Undefined function 'teraz' for input arguments of type 'char'.
 
>> transponowanie macierzy 
Undefined function 'transponowanie' for input arguments of type 'char'.
 
>> AT=A'

AT =

     1     4     7
     2     5     8
     3     6     9

>> help clear
 clear  Clear variables and functions from memory.
    clear removes all variables from the workspace.
    clear VARIABLES does the same thing.
    clear GLOBAL removes all global variables.
    clear FUNCTIONS removes all compiled MATLAB and MEX-functions.
 
    clear ALL removes all variables, globals, functions and MEX links.
    clear ALL at the command prompt also clears the base import list.
 
    clear IMPORT clears the base import list.  It can only be issued at the 
    command prompt. It cannot be used in a function.
 
    clear CLASSES is the same as clear ALL except that class definitions
    are also cleared. If any objects exist outside the workspace (say in 
    userdata or persistent in a locked program file) a warning will be
    issued and the class definition will not be cleared. clear CLASSES must
    be used if the number or names of fields in a class are changed.
 
    clear JAVA is the same as clear ALL except that java classes on the
    dynamic java path (defined using JAVACLASSPATH) are also cleared. 
 
    clear VAR1 VAR2 ... clears the variables specified. The wildcard
    character '*' can be used to clear variables that match a pattern. For
    instance, clear X* clears all the variables in the current workspace
    that start with X.
 
    clear -REGEXP PAT1 PAT2 can be used to match all patterns using regular
    expressions. This option only clears variables. For more information on
    using regular expressions, type "doc regexp" at the command prompt.
 
    If X is global, clear X removes X from the current workspace, but
    leaves it accessible to any functions declaring it global. 
    clear GLOBAL X completely removes the global variable X. 
    clear GLOBAL -REGEXP PAT removes global variables that match regular
    expression patterns.
    Note that to clear specific global variables, the GLOBAL option must
    come first. Otherwise, all global variables will be cleared.
 
    clear FUN clears the function specified. If FUN has been locked by
    MLOCK it will remain in memory. Use a partial path (see PARTIALPATH) to
    distinguish between different overloaded versions of FUN.  For
    instance, 'clear inline/display' clears only the INLINE method for
    DISPLAY, leaving any other implementations in memory.
 
    clear ALL, clear FUN, or clear FUNCTIONS also have the side effect of
    removing debugging breakpoints and reinitializing persistent variables
    since the breakpoints for a function and persistent variables are
    cleared whenever the program file changes or is cleared.
 
    Use the functional form of clear, such as clear('name'), when the
    variable name or function name is stored in a string.
 
    Examples for pattern matching:
        clear a*                % Clear variables starting with "a"
        clear -regexp ^b\d{3}$  % Clear variables starting with "b" and
                                %    followed by 3 digits
        clear -regexp \d        % Clear variables containing any digits
 
    See also clearvars, who, whos, mlock, munlock, persistent, import.

    Reference page in Help browser
       doc clear

>> diag(A)

ans =

     1
     5
     9

>> czyli glowna przekatna 
Undefined function 'czyli' for input arguments of type 'char'.
 
>> diag(AB)

ans =

     1
     5
     9

>> det(A)

ans =

   6.6613e-16

>> wyznacznik macierzy, proste 
Undefined function 'wyznacznik' for input arguments of type 'char'.
 
>> poznajemy operator zakresu, czyli range operator 
Undefined function 'poznajemy' for input arguments of type 'char'.
 
>> kiedy chcemy skopiowac fragment jakiejs wiekszej tablicy 
Undefined function 'kiedy' for input arguments of type 'char'.
 
>> AB2=[ A A A; B B B]

AB2 =

    1.0000    2.0000    3.0000    1.0000    2.0000    3.0000    1.0000    2.0000    3.0000
    4.0000    5.0000    6.0000    4.0000    5.0000    6.0000    4.0000    5.0000    6.0000
    7.0000    8.0000    9.0000    7.0000    8.0000    9.0000    7.0000    8.0000    9.0000
    2.0000   -1.0000    3.5000    2.0000   -1.0000    3.5000    2.0000   -1.0000    3.5000
   -0.1300   -0.3000    2.2000   -0.1300   -0.3000    2.2000   -0.1300   -0.3000    2.2000
    3.0000    0.5000   34.0000    3.0000    0.5000   34.0000    3.0000    0.5000   34.0000

>> size(AB2)

ans =

     6     9

>> Anowa = AB(2:5; 2:3)
 Anowa = AB(2:5; 2:3)
               |
Error: Unbalanced or unexpected parenthesis or bracket.
 
>> Anowa = AB(2:5,2:3)
Index exceeds matrix dimensions.
 
>> wiersz4 = AB2(4,1:9)

wiersz4 =

    2.0000   -1.0000    3.5000    2.0000   -1.0000    3.5000    2.0000   -1.0000    3.5000

>> wiersz41=AB2(4, :)

wiersz41 =

    2.0000   -1.0000    3.5000    2.0000   -1.0000    3.5000    2.0000   -1.0000    3.5000

>> kol2=AB@( : , 2)
 kol2=AB@( : , 2)
         |
Error: Unbalanced or unexpected parenthesis or bracket.
 
>> kol2=AB2(:,2)

kol2 =

    2.0000
    5.0000
    8.0000
   -1.0000
   -0.3000
    0.5000

>> kol2t=kol2'

kol2t =

    2.0000    5.0000    8.0000   -1.0000   -0.3000    0.5000

>> A

A =

     1     2     3
     4     5     6
     7     8     9

>> sum(A)

ans =

    12    15    18

>> sum(A')

ans =

     6    15    24

>> sum(A')'

ans =

     6
    15
    24

>> wektory - ciagi liczbowe 
 wektory - ciagi liczbowe 
                 |
Error: Unexpected MATLAB expression.
 
>> operator zakresu to dwukropek 
Undefined function 'operator' for input arguments of type 'char'.
 
>> k=0:10

k =

     0     1     2     3     4     5     6     7     8     9    10

>> k1=2:0.1:3.2

k1 =

  Columns 1 through 12

    2.0000    2.1000    2.2000    2.3000    2.4000    2.5000    2.6000    2.7000    2.8000    2.9000    3.0000    3.1000

  Column 13

    3.2000

>> czyli zaczynamy od 2 z krokiem co 0.1 i do 3.2
Undefined function 'czyli' for input arguments of type 'char'.
 
>> ciagx=2:5:49

ciagx =

     2     7    12    17    22    27    32    37    42    47

>> % (ogolnie: ciag = start :krok/przyrost: koncowa wartosc/koniec)
>> cl=1:0.7:12

cl =

  Columns 1 through 12

    1.0000    1.7000    2.4000    3.1000    3.8000    4.5000    5.2000    5.9000    6.6000    7.3000    8.0000    8.7000

  Columns 13 through 16

    9.4000   10.1000   10.8000   11.5000

>> size(cl)

ans =

     1    16

>> r=size(cl)

r =

     1    16

>> size(r)

ans =

     1     2

>> w=r(1,1)

w =

     1

>> kol=r(1,2)

kol =

    16

>> [w,k]=size(cl)

w =

     1


k =

    16

>> w

w =

     1

>> k

k =

    16

>> dl=length(cl)

dl =

    16

>> c2=1:-0.2:-1

c2 =

    1.0000    0.8000    0.6000    0.4000    0.2000         0   -0.2000   -0.4000   -0.6000   -0.8000   -1.0000

>> c3=-1:-0.2:1

c3 =

   Empty matrix: 1-by-0

>> k=0:20

k =

  Columns 1 through 20

     0     1     2     3     4     5     6     7     8     9    10    11    12    13    14    15    16    17    18    19

  Column 21

    20

>> kpol=0.5*k

kpol =

  Columns 1 through 12

         0    0.5000    1.0000    1.5000    2.0000    2.5000    3.0000    3.5000    4.0000    4.5000    5.0000    5.5000

  Columns 13 through 21

    6.0000    6.5000    7.0000    7.5000    8.0000    8.5000    9.0000    9.5000   10.0000

>> kk=5+k

kk =

  Columns 1 through 20

     5     6     7     8     9    10    11    12    13    14    15    16    17    18    19    20    21    22    23    24

  Column 21

    25

>> pi

ans =

    3.1416

>> i

ans =

   0.0000 + 1.0000i

>> j

ans =

   0.0000 + 1.0000i

>> %pi to taka predefiniowana stala, nie musimy dysponowac jej dokladna wartoscia
>> e
Undefined function or variable 'e'.
 
>> %kiedy wpisujemy "i" to jednostka urojona, podobnie dziala "j" 
>> %matlab dziala na liczbach rzeczywistych i zespolonych 
>> pi=50

pi =

    50

>> who

Your variables are:

A         AB2       B         Nowa      Suma      c2        dana      kk        kpol      wiersz4   
A10       ABB       Dziel     P         T         c3        dl        kol       pi        wiersz41  
AB        AP        Dziel1    POT       a         ciagx     k         kol2      r         
AB1       AT        Mnoz      Roz       ans       cl        k1        kol2t     w         

>> %po takiej operacji zmienna zablokuje nam dostep do predefiniowanej liczby pi 
>> %jak odzyskac dostep do liczby pi do jej normalnej wartosci?
>> %who maskuje dostep do predefinoiwanej jednostki, jezeli w komendzie, poleceniu pojawi sie nazwa zmiennej to wtedy matlab rozpoczyna przeszukiwanie i jesli jej nie nzajdzie szuka 
>> mx=max(A)

mx =

     7     8     9

>> mn=min(A)

mn =

     1     2     3

>> mmm=max(mx)  

mmm =

     9

>> mmm=max(max(A))

mmm =

     9

>> E=eye(4)

E =

     1     0     0     0
     0     1     0     0
     0     0     1     0
     0     0     0     1

>> %macierz jednostkowa
>> E1=eye(4,7)

E1 =

     1     0     0     0     0     0     0
     0     1     0     0     0     0     0
     0     0     1     0     0     0     0
     0     0     0     1     0     0     0

>> E1=eye(6,3)

E1 =

     1     0     0
     0     1     0
     0     0     1
     0     0     0
     0     0     0
     0     0     0

>> %magic robi ze wszystkie sumy wyrazow w wierszach i kolumnach sa jednakowe 
>> M=magic(6)

M =

    35     1     6    26    19    24
     3    32     7    21    23    25
    31     9     2    22    27    20
     8    28    33    17    10    15
    30     5    34    12    14    16
     4    36    29    13    18    11

>> w1=sum(M)

w1 =

   111   111   111   111   111   111

>> %sumowanie wartosci w kolumnach
>> w2=sum(M')

w2 =

   111   111   111   111   111   111

>> %sumowanie wartosci w wierszach
>> J=ones(3,6)

J =

     1     1     1     1     1     1
     1     1     1     1     1     1
     1     1     1     1     1     1

>> Z=zeros(4,5)

Z =

     0     0     0     0     0
     0     0     0     0     0
     0     0     0     0     0
     0     0     0     0     0

>> % stworzymy sobie kolejno wektor 4 zer a potem z 4 jedynek czy jakos tak
>> Z=zeros(1,4)

Z =

     0     0     0     0

>> J=ones(1,4)

J =

     1     1     1     1

>> okres=[J,Z]

okres =

     1     1     1     1     0     0     0     0

>> syg=[okres, okres, okres, okres, okres]

syg =

  Columns 1 through 20

     1     1     1     1     0     0     0     0     1     1     1     1     0     0     0     0     1     1     1     1

  Columns 21 through 40

     0     0     0     0     1     1     1     1     0     0     0     0     1     1     1     1     0     0     0     0

>> length(syg)

ans =

    40

>> %uzywanie petli - macierz pusta 
>> sygnal =[]

sygnal =

     []

>> for i=1:10
sygnal=[sygnal;okres]
end

sygnal =

     1     1     1     1     0     0     0     0


sygnal =

     1     1     1     1     0     0     0     0
     1     1     1     1     0     0     0     0


sygnal =

     1     1     1     1     0     0     0     0
     1     1     1     1     0     0     0     0
     1     1     1     1     0     0     0     0


sygnal =

     1     1     1     1     0     0     0     0
     1     1     1     1     0     0     0     0
     1     1     1     1     0     0     0     0
     1     1     1     1     0     0     0     0


sygnal =

     1     1     1     1     0     0     0     0
     1     1     1     1     0     0     0     0
     1     1     1     1     0     0     0     0
     1     1     1     1     0     0     0     0
     1     1     1     1     0     0     0     0


sygnal =

     1     1     1     1     0     0     0     0
     1     1     1     1     0     0     0     0
     1     1     1     1     0     0     0     0
     1     1     1     1     0     0     0     0
     1     1     1     1     0     0     0     0
     1     1     1     1     0     0     0     0


sygnal =

     1     1     1     1     0     0     0     0
     1     1     1     1     0     0     0     0
     1     1     1     1     0     0     0     0
     1     1     1     1     0     0     0     0
     1     1     1     1     0     0     0     0
     1     1     1     1     0     0     0     0
     1     1     1     1     0     0     0     0


sygnal =

     1     1     1     1     0     0     0     0
     1     1     1     1     0     0     0     0
     1     1     1     1     0     0     0     0
     1     1     1     1     0     0     0     0
     1     1     1     1     0     0     0     0
     1     1     1     1     0     0     0     0
     1     1     1     1     0     0     0     0
     1     1     1     1     0     0     0     0


sygnal =

     1     1     1     1     0     0     0     0
     1     1     1     1     0     0     0     0
     1     1     1     1     0     0     0     0
     1     1     1     1     0     0     0     0
     1     1     1     1     0     0     0     0
     1     1     1     1     0     0     0     0
     1     1     1     1     0     0     0     0
     1     1     1     1     0     0     0     0
     1     1     1     1     0     0     0     0


sygnal =

     1     1     1     1     0     0     0     0
     1     1     1     1     0     0     0     0
     1     1     1     1     0     0     0     0
     1     1     1     1     0     0     0     0
     1     1     1     1     0     0     0     0
     1     1     1     1     0     0     0     0
     1     1     1     1     0     0     0     0
     1     1     1     1     0     0     0     0
     1     1     1     1     0     0     0     0
     1     1     1     1     0     0     0     0

>> help randn
 randn Normally distributed pseudorandom numbers.
    R = randn(N) returns an N-by-N matrix containing pseudorandom values drawn
    from the standard normal distribution.  randn(M,N) or randn([M,N]) returns
    an M-by-N matrix. randn(M,N,P,...) or randn([M,N,P,...]) returns an
    M-by-N-by-P-by-... array. randn returns a scalar.  randn(SIZE(A)) returns
    an array the same size as A.
 
    Note: The size inputs M, N, P, ... should be nonnegative integers.
    Negative integers are treated as 0.
 
    R = randn(..., 'double') or R = randn(..., 'single') returns an array of
    normal values of the specified class.
 
    The sequence of numbers produced by randn is determined by the settings of
    the uniform random number generator that underlies RAND, randn, and RANDI.
    randn uses one or more uniform random values to create each normal random
    value.  Control that shared random number generator using RNG.
  
    Examples:
 
       Example 1: Generate values from a normal distribution with mean 1
        and standard deviation 2.
          r = 1 + 2.*randn(100,1);
 
       Example 2: Generate values from a bivariate normal distribution with
       specified mean vector and covariance matrix.
          mu = [1 2];
          Sigma = [1 .5; .5 2]; R = chol(Sigma);
          z = repmat(mu,100,1) + randn(100,2)*R;
 
       Example 3: Reset the random number generator used by RAND, RANDI, and
       randn to its default startup settings, so that randn produces the same
       random numbers as if you restarted MATLAB.
          rng('default');
          randn(1,5)
 
       Example 4: Save the settings for the random number generator used by
       RAND, RANDI, and randn, generate 5 values from randn, restore the
       settings, and repeat those values.
          s = rng
          z1 = randn(1,5)
          rng(s);
          z2 = randn(1,5) % z2 contains exactly the same values as z1
 
       Example 5: Reinitialize the random number generator used by RAND,
       RANDI, and randn with a seed based on the current time.  randn will
       return different values each time you do this.  NOTE: It is usually
       not necessary to do this more than once per MATLAB session.
          rng('shuffle');
          randn(1,5)
 
    See Updating Your Random Number Generator Syntax to use RNG to replace
    randn with the 'seed' or 'state' inputs.
 
    See also rand, randi, rng, RandStream, RandStream/randn

    Overloaded methods:
       RandStream/randn
       distributed/randn
       codistributor2dbc/randn
       codistributor1d/randn
       codistributed/randn
       gpuArray/randn

    Reference page in Help browser
       doc randn

>> %funkcja randn zwraca probki o rozkladzie noramlnym, czyli gaussowaskim 
>> szum=randn(1,10)

szum =

    0.5377    1.8339   -2.2588    0.8622    0.3188   -1.3077   -0.4336    0.3426    3.5784    2.7694

>> %sygnal losowy o rozkladzie gaussowskim 
>> szum_rown=rand(2,5)

szum_rown =

    0.1576    0.9572    0.8003    0.4218    0.7922
    0.9706    0.4854    0.1419    0.9157    0.9595

>> % wyzej - sygnal o rozkladzie rownomiernym 
>> %na przedziale ten sygnal jest 0 , 1
>> srednia = mean(szum)

srednia =

    0.6243

>> %wartosc srednia 
>> szum=randn(1,1000); srednia=mean(szum) 

srednia =

   -0.0460

>> %cztery funkcje ktore dotycza zaokraglenie
>> ceil(5.3)

ans =

     6

>> %zawsdze w gore
>> floor(3.8)

ans =

     3

>> fix(6.7) 

ans =

     6

>> fix(-4.8)

ans =

    -4

>> %zawsze w kierunku zera - fix 
>> round(13.4) 

ans =

    13

>> %round zaokraglenie
>> fix(2.7)

ans =

     2

>> round(2.7)

ans =

     3

>> %TABLICE ZNAKOWE 
>> txt1='Ulubiona ksiazka'

txt1 =

Ulubiona ksiazka

>> txt2='Ala ma kota'

txt2 =

Ala ma kota

>> tekst = [txt1, ':', txt2] 

tekst =

Ulubiona ksiazka:Ala ma kota

>> tekst = [txt1, ' : ', txt2]

tekst =

Ulubiona ksiazka : Ala ma kota

>> %symulacja rzutu kostka 
>> rzut=rand(1,1)

rzut =

    0.5301

>> rzut=6*rand(1,1)

rzut =

    1.6504

>> rzut=floor(6*rand(1,1))

rzut =

     1

>> rzut=floor(rand(1,1)) +1 

rzut =

     1

>> rzut = floor(6*rand(1,5)) +1 

rzut =

     2     5     6     1     4

>> rzut = floor(6*rand(1,5)) +1

rzut =

     1     5     6     1     6

>> rzut = floor(6*rand(1,5)) +1

rzut =

     1     5     5     4     6

>> rzut = floor(6*rand(1,5)) +1

rzut =

     6     4     1     2     2

>> rzut = floor(6*rand(1,5)) +1

rzut =

     1     1     4     6     3

>> rzut = floor(6*rand(1,5)) +1

rzut =

     3     6     6     5     6

>> %za kazdym nastepnym razem wywolanai tej funkcja sa inne wartosci 
>> %FUNKCJE TRYGONOMETRYCZNE
>> A=3 %amplituda

A =

     3

>> f=2 %czestotliwosc

f =

     2

>> t=0:0.01:1 %wektor czasu

t =

  Columns 1 through 12

         0    0.0100    0.0200    0.0300    0.0400    0.0500    0.0600    0.0700    0.0800    0.0900    0.1000    0.1100

  Columns 13 through 24

    0.1200    0.1300    0.1400    0.1500    0.1600    0.1700    0.1800    0.1900    0.2000    0.2100    0.2200    0.2300

  Columns 25 through 36

    0.2400    0.2500    0.2600    0.2700    0.2800    0.2900    0.3000    0.3100    0.3200    0.3300    0.3400    0.3500

  Columns 37 through 48

    0.3600    0.3700    0.3800    0.3900    0.4000    0.4100    0.4200    0.4300    0.4400    0.4500    0.4600    0.4700

  Columns 49 through 60

    0.4800    0.4900    0.5000    0.5100    0.5200    0.5300    0.5400    0.5500    0.5600    0.5700    0.5800    0.5900

  Columns 61 through 72

    0.6000    0.6100    0.6200    0.6300    0.6400    0.6500    0.6600    0.6700    0.6800    0.6900    0.7000    0.7100

  Columns 73 through 84

    0.7200    0.7300    0.7400    0.7500    0.7600    0.7700    0.7800    0.7900    0.8000    0.8100    0.8200    0.8300

  Columns 85 through 96

    0.8400    0.8500    0.8600    0.8700    0.8800    0.8900    0.9000    0.9100    0.9200    0.9300    0.9400    0.9500

  Columns 97 through 101

    0.9600    0.9700    0.9800    0.9900    1.0000

>> s=A*sin(2*pi*f*t) % sygnal

s =

  Columns 1 through 12

         0    2.7279   -2.2704   -0.8382    2.9681   -1.6321   -1.6097    2.9718   -0.8637   -2.2530    2.7388   -0.0266

  Columns 13 through 24

   -2.7167    2.2877    0.8127   -2.9641    1.6543    1.5872   -2.9753    0.8891    2.2353   -2.7496    0.0531    2.7054

  Columns 25 through 36

   -2.3048   -0.7871    2.9599   -1.6764   -1.5647    2.9786   -0.9144   -2.2175    2.7601   -0.0797   -2.6938    2.3217

  Columns 37 through 48

    0.7615   -2.9554    1.6983    1.5419   -2.9817    0.9397    2.1996   -2.7704    0.1062    2.6820   -2.3384   -0.7358

  Columns 49 through 60

    2.9508   -1.7201   -1.5191    2.9845   -0.9649   -2.1814    2.7805   -0.1327   -2.6700    2.3549    0.7100   -2.9459

  Columns 61 through 72

    1.7418    1.4961   -2.9871    0.9900    2.1631   -2.7903    0.1593    2.6578   -2.3713   -0.6842    2.9407   -1.7634

  Columns 73 through 84

   -1.4731    2.9894   -1.0150   -2.1446    2.8000   -0.1858   -2.6454    2.3875    0.6583   -2.9354    1.7848    1.4499

  Columns 85 through 96

   -2.9915    1.0399    2.1260   -2.8094    0.2123    2.6327   -2.4035   -0.6323    2.9298   -1.8061   -1.4266    2.9934

  Columns 97 through 101

   -1.0648   -2.1072    2.8186   -0.2387   -2.6199

>> plot(t,s)
>> grid on
>> %ZAPIS DO PLIKU

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