(* Content-type: application/mathematica *)

(*** Wolfram Notebook File ***)
(* http://www.wolfram.com/nb *)

(* CreatedBy='Mathematica 6.0' *)

(*CacheID: 234*)
(* Internal cache information:
NotebookFileLineBreakTest
NotebookFileLineBreakTest
NotebookDataPosition[       145,          7]
NotebookDataLength[    238439,       4742]
NotebookOptionsPosition[    235178,       4637]
NotebookOutlinePosition[    235913,       4663]
CellTagsIndexPosition[    235870,       4660]
WindowFrame->Normal
ContainsDynamic->False*)

(* Beginning of Notebook Content *)
Notebook[{
Cell[BoxData[
 StyleBox[
  RowBox[{"2.2", ".3", " ", 
   RowBox[{
    StyleBox["Mathematica",
     FontSlant->"Italic"], ":", 
    "\:30d5\:30fc\:30ea\:30a8\:5909\:63db\:30fb\:7a4d\:5206"}]}],
  FontSize->18]], "Input"],

Cell[BoxData[{
 RowBox[{"FourierTransform", "  ", "\:306f\:ff0c", 
  SqrtBox[
   FractionBox[
    RowBox[{"|", "b", "|"}], 
    SuperscriptBox[
     RowBox[{"(", 
      RowBox[{"2", "\[Pi]"}], ")"}], 
     RowBox[{"1", "-", "a"}]]]], 
  RowBox[{
   SubsuperscriptBox["\[Integral]", 
    RowBox[{"-", "\[Infinity]"}], "\[Infinity]"], 
   RowBox[{"f", 
    RowBox[{"(", "t", ")"}], 
    SuperscriptBox["\[ExponentialE]", "ib\[Omega]t"], 
    RowBox[{"\[DifferentialD]", "t"}]}]}]}], "\[IndentingNewLine]", 
 RowBox[{"FourierCosTransform", "  ", "\:306f\:ff0c2", 
  SqrtBox[
   FractionBox[
    RowBox[{"|", "b", "|"}], 
    SuperscriptBox[
     RowBox[{"(", 
      RowBox[{"2", "\[Pi]"}], ")"}], 
     RowBox[{"1", "-", "a"}]]]], 
  RowBox[{
   SubsuperscriptBox["\[Integral]", 
    RowBox[{"-", "\[Infinity]"}], "\[Infinity]"], 
   RowBox[{"f", 
    RowBox[{"(", "t", ")"}], 
    RowBox[{"Cos", "[", "b\[Omega]t", "]"}], 
    RowBox[{"\[DifferentialD]", "t"}]}]}]}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{
  "\:3068\:5b9a\:7fa9\:3055\:308c\:3066\:3044\:307e\:3059\:ff0e\:30c7\:30d5\
\:30a9\:30eb\:30c8\:306f", "  ", "FourierParameters"}], "\[Rule]", 
  RowBox[{
   RowBox[{"{", 
    RowBox[{"0", ",", "1"}], "}"}], " ", 
   "\:3067"}]}], "\[IndentingNewLine]", 
 RowBox[{
  FractionBox["1", 
   SqrtBox[
    RowBox[{"2", "\[Pi]"}]]], 
  RowBox[{
   SubsuperscriptBox["\[Integral]", 
    RowBox[{"-", "\[Infinity]"}], "\[Infinity]"], 
   RowBox[{"f", 
    RowBox[{"(", "t", ")"}], 
    SuperscriptBox["\[ExponentialE]", "i\[Omega]t"], 
    RowBox[{
    "\[DifferentialD]", 
     "t\:3092\:6c42\:3081\:307e\:3059\:ff0e"}]}]}]}], "\[IndentingNewLine]", 
 RowBox[{"\:672c\:66f8\:3067\:306f\:4ee5\:4e0b\:ff0cFourierTransform", "  ", 
  "\:306f\:ff0c"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{"FourierParameters", "\[Rule]", 
   RowBox[{
    RowBox[{"{", 
     RowBox[{"1", ",", 
      RowBox[{"-", "1"}]}], "}"}], "  ", "\:3068\:3057\:ff0c", 
    RowBox[{
     SubsuperscriptBox["\[Integral]", 
      RowBox[{"-", "\[Infinity]"}], "\[Infinity]"], 
     RowBox[{"f", 
      RowBox[{"(", "t", ")"}], 
      SuperscriptBox["\[ExponentialE]", 
       RowBox[{"-", "i\[Omega]t"}]], 
      RowBox[{"\[DifferentialD]", "t"}], " ", 
      "\:3092\:6c42\:3081\:307e\:3059\:ff0e"}]}]}]}], 
  "\[IndentingNewLine]"}], "\[IndentingNewLine]", 
 RowBox[{"\:4efb\:610f\:306e\:95a2\:6570\:306e\:30d5\:30fc\:30ea\:30a8\:5909\
\:63db\:3092\:8a08\:7b97\:3059\:308b\:306e\:306b", " ", 
  RowBox[{"Ft", "[", "f_", "]"}], 
  "\:3092\:5b9a\:7fa9\:3057\:3066\:304a\:304d\:307e\:3059\:ff0e"}], "\n", "\
\:3053\:308c\:3092\:4f7f\:3063\:3066\:ff0c\:3044\:304f\:3064\:304b\:306e\:95a2\
\:6570\:306e\:30d5\:30fc\:30ea\:30a8\:5909\:63db\:3092\:8868\:306b\:3057\:3066\
\:307f\:307e\:3059\:ff0e"}], "Input",
 CellDingbat->"\[FilledSquare]",
 CellChangeTimes->{3.4111142540027266`*^9},
 FontVariations->{"CompatibilityType"->0},
 Background->RGBColor[
  0.4666666666666667, 0.8352941176470589, 0.8235294117647058]],

Cell[BoxData[
 RowBox[{"<<", "\"\<FourierSeries`\>\""}]], "Input",
 CellChangeTimes->{{3.409471129039*^9, 3.409471148882*^9}, {3.409471204398*^9,
    3.4094712323120003`*^9}, {3.409471358741*^9, 3.409471366384*^9}, 
   3.409471412677*^9, {3.4095525961926603`*^9, 3.40955261167666*^9}, {
   3.40955279336266*^9, 3.40955279891966*^9}, {3.409637955603855*^9, 
   3.409637976017855*^9}},
 CellLabel->"In[1]:="],

Cell["\<\
a=.;Delta=DiracDelta;ns= HeavisideTheta;
Ft[f_]:=FourierTransform[f,t,\[Omega],FourierParameters\[Rule]{1,-1}]
//FullSimplify;\
\>", "Input",
 CellChangeTimes->{
  3.409471003571*^9, {3.40955340945266*^9, 3.40955341059966*^9}, {
   3.40955344970866*^9, 3.40955345095866*^9}, {3.411360062178879*^9, 
   3.411360068594879*^9}, 3.413948306933*^9, 3.413948532867*^9},
 CellLabel->"In[2]:="],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{
  RowBox[{GridBox[{
     {"1.", 
      RowBox[{"Ft", "[", 
       RowBox[{"Cos", "[", 
        RowBox[{"a", " ", "t"}], "]"}], "]"}], "2.", 
      RowBox[{"Ft", "[", 
       RowBox[{"Sin", "[", 
        RowBox[{"a", " ", "t"}], "]"}], "]"}]},
     {"3.", 
      RowBox[{"Ft", "[", 
       RowBox[{"Cos", "[", 
        SuperscriptBox["t", "2"], "]"}], "]"}], "4.", 
      RowBox[{"Ft", "[", 
       RowBox[{"Sin", "[", 
        SuperscriptBox["t", "2"], "]"}], "]"}]},
     {"5.", 
      RowBox[{"Ft", "[", 
       RowBox[{"ns", "[", "t", "]"}], "]"}], "6.", 
      RowBox[{"Ft", "[", 
       RowBox[{
        RowBox[{"ns", "[", 
         RowBox[{"t", "+", "a"}], "]"}], "-", 
        RowBox[{"ns", "[", 
         RowBox[{"t", "-", "a"}], "]"}]}], "]"}]},
     {"7.", 
      RowBox[{"Ft", "[", 
       RowBox[{"Delta", "[", "t", "]"}], "]"}], "8.", 
      RowBox[{"Ft", "[", 
       RowBox[{
        RowBox[{"Delta", "[", 
         RowBox[{"t", "+", "a"}], "]"}], "-", 
        RowBox[{"Delta", "[", 
         RowBox[{"t", "-", "a"}], "]"}]}], "]"}]},
     {"9.", 
      RowBox[{"Ft", "[", 
       FractionBox["1", 
        RowBox[{
         SuperscriptBox["t", "2"], "+", 
         SuperscriptBox["a", "2"]}]], "]"}], "10.", 
      RowBox[{"Ft", "[", 
       FractionBox["t", 
        RowBox[{
         SuperscriptBox["t", "2"], "+", 
         SuperscriptBox["a", "2"]}]], "]"}]},
     {"11.", 
      RowBox[{"Ft", "[", 
       RowBox[{"Exp", "[", 
        RowBox[{"-", 
         RowBox[{"Abs", "[", "t", "]"}]}], "]"}], "]"}], "12.", 
      RowBox[{"Ft", "[", 
       RowBox[{"Exp", "[", 
        RowBox[{"-", 
         SuperscriptBox["t", "2"]}], "]"}], "]"}]},
     {"13.", 
      RowBox[{"Ft", "[", "t", "]"}], "14.", 
      RowBox[{"Ft", "[", 
       SuperscriptBox["t", "2"], "]"}]},
     {"15.", 
      RowBox[{"Ft", "[", 
       RowBox[{
        RowBox[{"f", "'"}], "[", "t", "]"}], "]"}], "16.", 
      RowBox[{"Ft", "[", 
       RowBox[{"D", "[", 
        RowBox[{
         RowBox[{"f", "[", "t", "]"}], ",", 
         RowBox[{"{", 
          RowBox[{"t", ",", "3"}], "}"}]}], "]"}], "]"}]}
    },
    GridBoxDividers->{
     "Columns" -> {{True}}, "ColumnsIndexed" -> {}, "Rows" -> {{True}}, 
      "RowsIndexed" -> {}}], "/.", 
   RowBox[{"{", 
    RowBox[{
     RowBox[{
      RowBox[{"FourierTransform", "[", 
       RowBox[{
        RowBox[{"f", "[", "t", "]"}], ",", "t", ",", "\[Omega]"}], "]"}], 
      "\[Rule]", 
      RowBox[{"F", "[", "\[Omega]", "]"}]}], ",", 
     RowBox[{
      RowBox[{"DiracDelta", "[", "\[Omega]", "]"}], "\[Rule]", 
      RowBox[{"\[Delta]", "[", "\[Omega]", "]"}]}], ",", 
     RowBox[{
      RowBox[{"\[Pi]", " ", 
       RowBox[{"DiracDelta", "[", "\[Omega]", "]"}]}], "\[Rule]", 
      RowBox[{"\[Pi]\[Delta]", "[", "\[Omega]", "]"}]}], ",", 
     RowBox[{
      RowBox[{"\[Pi]", " ", 
       RowBox[{"DiracDelta", "[", 
        RowBox[{"a", "-", "\[Omega]"}], "]"}]}], "\[Rule]", 
      RowBox[{"\[Pi]\[Delta]", "[", 
       RowBox[{"a", "-", "\[Omega]"}], "]"}]}], ",", 
     RowBox[{
      RowBox[{"\[Pi]", " ", 
       RowBox[{"DiracDelta", "[", 
        RowBox[{"a", "+", "\[Omega]"}], "]"}]}], "\[Rule]", 
      RowBox[{"\[Pi]\[Delta]", "[", 
       RowBox[{"a", "+", "\[Omega]"}], "]"}]}], ",", " ", 
     RowBox[{
      RowBox[{"HeavisideTheta", "[", 
       RowBox[{"\[Omega]", " ", 
        RowBox[{"Sign", "[", 
         RowBox[{"Re", "[", "a", "]"}], "]"}]}], "]"}], "\[Rule]", 
      RowBox[{"u", "[", "a\[Omega]", "]"}]}], ",", " ", 
     RowBox[{
      RowBox[{"HeavisideTheta", "[", 
       RowBox[{
        RowBox[{"-", "\[Omega]"}], " ", 
        RowBox[{"Sign", "[", 
         RowBox[{"Re", "[", "a", "]"}], "]"}]}], "]"}], "\[Rule]", 
      RowBox[{"u", "[", 
       RowBox[{"-", "a\[Omega]"}], "]"}]}]}], "}"}]}], 
  ";"}], "\[IndentingNewLine]", 
 RowBox[{"TableForm", "[", 
  RowBox[{"%", ",", 
   RowBox[{"TableSpacing", "\[Rule]", 
    RowBox[{"{", 
     RowBox[{"1", ",", "1"}], "}"}]}]}], "]"}]}], "Input",
 CellChangeTimes->{{3.4094708260769997`*^9, 3.409470831672*^9}, {
  3.40955278215366*^9, 3.40955278844066*^9}, {3.40955304295366*^9, 
  3.40955307784966*^9}, {3.409638044610855*^9, 3.409638046065855*^9}},
 CellLabel->"In[4]:="],

Cell[BoxData[
 TagBox[GridBox[{
    {"1.`", 
     RowBox[{
      RowBox[{"\[Pi]\[Delta]", "[", 
       RowBox[{"a", "-", "\[Omega]"}], "]"}], "+", 
      RowBox[{"\[Pi]\[Delta]", "[", 
       RowBox[{"a", "+", "\[Omega]"}], "]"}]}], "2.`", 
     RowBox[{
      RowBox[{
       RowBox[{"-", "\[ImaginaryI]"}], " ", 
       RowBox[{"\[Pi]\[Delta]", "[", 
        RowBox[{"a", "-", "\[Omega]"}], "]"}]}], "+", 
      RowBox[{"\[ImaginaryI]", " ", 
       RowBox[{"\[Pi]\[Delta]", "[", 
        RowBox[{"a", "+", "\[Omega]"}], "]"}]}]}]},
    {"3.`", 
     RowBox[{
      SqrtBox[
       FractionBox["\[Pi]", "2"]], " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"Cos", "[", 
         FractionBox[
          SuperscriptBox["\[Omega]", "2"], "4"], "]"}], "+", 
        RowBox[{"Sin", "[", 
         FractionBox[
          SuperscriptBox["\[Omega]", "2"], "4"], "]"}]}], ")"}]}], "4.`", 
     RowBox[{
      SqrtBox[
       FractionBox["\[Pi]", "2"]], " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"Cos", "[", 
         FractionBox[
          SuperscriptBox["\[Omega]", "2"], "4"], "]"}], "-", 
        RowBox[{"Sin", "[", 
         FractionBox[
          SuperscriptBox["\[Omega]", "2"], "4"], "]"}]}], ")"}]}]},
    {"5.`", 
     RowBox[{
      RowBox[{"-", 
       FractionBox["\[ImaginaryI]", "\[Omega]"]}], "+", 
      RowBox[{"\[Pi]\[Delta]", "[", "\[Omega]", "]"}]}], "6.`", 
     FractionBox[
      RowBox[{"2", " ", 
       RowBox[{"Sin", "[", 
        RowBox[{"a", " ", "\[Omega]"}], "]"}]}], "\[Omega]"]},
    {"7.`", "1", "8.`", 
     RowBox[{"2", " ", "\[ImaginaryI]", " ", 
      RowBox[{"Sin", "[", 
       RowBox[{"a", " ", "\[Omega]"}], "]"}]}]},
    {"9.`", 
     FractionBox[
      RowBox[{
       SuperscriptBox["\[ExponentialE]", 
        RowBox[{
         RowBox[{"-", "a"}], " ", "\[Omega]"}]], " ", "\[Pi]", " ", 
       RowBox[{"Sign", "[", 
        RowBox[{"Re", "[", "a", "]"}], "]"}], " ", 
       RowBox[{"(", 
        RowBox[{
         RowBox[{
          SuperscriptBox["\[ExponentialE]", 
           RowBox[{"2", " ", "a", " ", "\[Omega]"}]], " ", 
          RowBox[{"u", "[", 
           RowBox[{"-", "a\[Omega]"}], "]"}]}], "+", 
         RowBox[{"u", "[", "a\[Omega]", "]"}]}], ")"}]}], "a"], "10.`", 
     RowBox[{"\[ImaginaryI]", " ", 
      SuperscriptBox["\[ExponentialE]", 
       RowBox[{
        RowBox[{"-", "a"}], " ", "\[Omega]"}]], " ", "\[Pi]", " ", 
      RowBox[{"Sign", "[", 
       RowBox[{"Re", "[", "a", "]"}], "]"}], " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{
         SuperscriptBox["\[ExponentialE]", 
          RowBox[{"2", " ", "a", " ", "\[Omega]"}]], " ", 
         RowBox[{"u", "[", 
          RowBox[{"-", "a\[Omega]"}], "]"}]}], "-", 
        RowBox[{"u", "[", "a\[Omega]", "]"}]}], ")"}]}]},
    {"11.`", 
     FractionBox["2", 
      RowBox[{"1", "+", 
       SuperscriptBox["\[Omega]", "2"]}]], "12.`", 
     RowBox[{
      SuperscriptBox["\[ExponentialE]", 
       RowBox[{"-", 
        FractionBox[
         SuperscriptBox["\[Omega]", "2"], "4"]}]], " ", 
      SqrtBox["\[Pi]"]}]},
    {"13.`", 
     RowBox[{"2", " ", "\[ImaginaryI]", " ", "\[Pi]", " ", 
      RowBox[{
       SuperscriptBox["DiracDelta", "\[Prime]",
        MultilineFunction->None], "[", "\[Omega]", "]"}]}], "14.`", 
     RowBox[{
      RowBox[{"-", "2"}], " ", "\[Pi]", " ", 
      RowBox[{
       SuperscriptBox["DiracDelta", "\[Prime]\[Prime]",
        MultilineFunction->None], "[", "\[Omega]", "]"}]}]},
    {"15.`", 
     RowBox[{"\[ImaginaryI]", " ", "\[Omega]", " ", 
      RowBox[{"F", "[", "\[Omega]", "]"}]}], "16.`", 
     RowBox[{
      RowBox[{"-", "\[ImaginaryI]"}], " ", 
      SuperscriptBox["\[Omega]", "3"], " ", 
      RowBox[{"F", "[", "\[Omega]", "]"}]}]}
   },
   GridBoxAlignment->{
    "Columns" -> {{Left}}, "ColumnsIndexed" -> {}, "Rows" -> {{Baseline}}, 
     "RowsIndexed" -> {}},
   GridBoxSpacings->{"Columns" -> {
       Offset[0.27999999999999997`], {
        Offset[0.7]}, 
       Offset[0.27999999999999997`]}, "ColumnsIndexed" -> {}, "Rows" -> {
       Offset[0.2], {
        Offset[0.4]}, 
       Offset[0.2]}, "RowsIndexed" -> {}}],
  Function[BoxForm`e$, 
   TableForm[BoxForm`e$, TableSpacing -> {1, 1}]]]], "Output",
 CellChangeTimes->{3.413948338434*^9},
 CellLabel->"Out[5]//TableForm="]
}, Open  ]],

Cell["", "PageBreak",
 PageBreakBelow->True],

Cell[BoxData["\:3044\:3064\:3064\:304b\:306e\:95a2\:6570\:3068\:30d5\:30fc\
\:30ea\:30a8\:5909\:63db\:306e\:30b0\:30e9\:30d5\:306e\:91cd\:306d\:304c\:304d\
"], "Input",
 CellDingbat->"\[FilledSquare]",
 Background->RGBColor[
  0.4666666666666667, 0.8352941176470589, 0.8235294117647058]],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{
  RowBox[{"a", "=", "1"}], ";", 
  RowBox[{"op", "=", 
   RowBox[{"{", 
    RowBox[{
     RowBox[{"AxesLabel", "\[Rule]", 
      RowBox[{"{", 
       RowBox[{"\"\<t,\[Omega]\>\"", ",", "\"\<f(t), F(\[Omega])\>\""}], 
       "}"}]}], ",", 
     RowBox[{"PlotStyle", "\[Rule]", 
      RowBox[{"{", 
       RowBox[{"Black", ",", 
        RowBox[{"{", 
         RowBox[{"Black", ",", 
          RowBox[{"Thickness", "[", "0.016", "]"}]}], "}"}]}], "}"}]}], ",", 
     RowBox[{"PlotRange", "\[Rule]", 
      RowBox[{"{", 
       RowBox[{
        RowBox[{"-", "2"}], ",", "2"}], "}"}]}]}], "}"}]}], ";"}], "\n", 
 RowBox[{
  RowBox[{"z4", "=", 
   RowBox[{"Plot", "[", 
    RowBox[{
     RowBox[{"{", 
      RowBox[{
       RowBox[{"Sin", "[", 
        SuperscriptBox["\[Omega]", "2"], "]"}], ",", 
       RowBox[{
        SqrtBox[
         FractionBox["\[Pi]", "2"]], " ", 
        RowBox[{"(", 
         RowBox[{
          RowBox[{"Cos", "[", 
           FractionBox[
            SuperscriptBox["\[Omega]", "2"], "4"], "]"}], "-", 
          RowBox[{"Sin", "[", 
           FractionBox[
            SuperscriptBox["\[Omega]", "2"], "4"], "]"}]}], ")"}]}]}], "}"}], 
     ",", 
     RowBox[{"{", 
      RowBox[{"\[Omega]", ",", 
       RowBox[{
        RowBox[{"-", "3"}], " ", "\[Pi]"}], ",", 
       RowBox[{"3", " ", "\[Pi]"}]}], "}"}], ",", 
     RowBox[{"Evaluate", "[", "op", "]"}]}], "]"}]}], ";"}], "\n", 
 RowBox[{
  RowBox[{"z6", "=", 
   RowBox[{"Plot", "[", 
    RowBox[{
     RowBox[{"{", " ", 
      RowBox[{
       RowBox[{
        RowBox[{"HeavisideTheta", "[", 
         RowBox[{"\[Omega]", "+", "a"}], "]"}], "-", " ", 
        RowBox[{"HeavisideTheta", "[", 
         RowBox[{"\[Omega]", "-", "a"}], "]"}]}], ",", 
       FractionBox[
        RowBox[{"2", " ", 
         RowBox[{"Sin", "[", 
          RowBox[{"a", " ", "\[Omega]"}], "]"}]}], "\[Omega]"]}], "}"}], ",", 
     
     RowBox[{"{", 
      RowBox[{"\[Omega]", ",", 
       RowBox[{
        RowBox[{"-", "3"}], " ", "\[Pi]"}], ",", 
       RowBox[{"3", " ", "\[Pi]"}]}], "}"}], ",", 
     RowBox[{"Evaluate", "[", "op", "]"}]}], "]"}]}], ";"}], "\n", 
 RowBox[{
  RowBox[{"z8", "=", 
   RowBox[{"Plot", "[", 
    RowBox[{
     RowBox[{"{", 
      RowBox[{
       RowBox[{
        RowBox[{"DiracDelta", "[", 
         RowBox[{"\[Omega]", "+", "a"}], "]"}], "-", 
        RowBox[{"DiracDelta", "[", 
         RowBox[{"\[Omega]", "-", "a"}], "]"}]}], ",", 
       RowBox[{"Abs", "[", 
        RowBox[{"2", " ", "\[ImaginaryI]", " ", 
         RowBox[{"Sin", "[", 
          RowBox[{"a", " ", "\[Omega]"}], "]"}]}], "]"}]}], "}"}], ",", 
     RowBox[{"{", 
      RowBox[{"\[Omega]", ",", 
       RowBox[{
        RowBox[{"-", "3"}], " ", "\[Pi]"}], ",", 
       RowBox[{"3", " ", "\[Pi]"}]}], "}"}], ",", 
     RowBox[{"Evaluate", "[", "op", "]"}]}], "]"}]}], ";"}], "\n", 
 RowBox[{
  RowBox[{"z9", "=", 
   RowBox[{"Plot", "[", 
    RowBox[{
     RowBox[{"{", 
      RowBox[{
       FractionBox["1", 
        RowBox[{
         SuperscriptBox["\[Omega]", "2"], "+", 
         SuperscriptBox["a", "2"]}]], ",", 
       RowBox[{
        FractionBox["1", "a"], 
        RowBox[{
         SuperscriptBox["\[ExponentialE]", 
          RowBox[{
           RowBox[{"-", "a"}], " ", "\[Omega]"}]], " ", "\[Pi]", " ", 
         RowBox[{"Sign", "[", 
          RowBox[{"Re", "[", "a", "]"}], "]"}], " ", 
         RowBox[{"(", 
          RowBox[{
           RowBox[{
            SuperscriptBox["\[ExponentialE]", 
             RowBox[{"2", " ", "a", " ", "\[Omega]"}]], 
            RowBox[{"HeavisideTheta", "[", 
             RowBox[{
              RowBox[{"-", "\[Omega]"}], " ", 
              RowBox[{"Sign", "[", 
               RowBox[{"Re", "[", "a", "]"}], "]"}]}], "]"}]}], "+", 
           RowBox[{"HeavisideTheta", "[", 
            RowBox[{"\[Omega]", " ", 
             RowBox[{"Sign", "[", 
              RowBox[{"Re", "[", "a", "]"}], "]"}]}], "]"}]}], ")"}]}]}]}], 
      "}"}], ",", 
     RowBox[{"{", 
      RowBox[{"\[Omega]", ",", 
       RowBox[{
        RowBox[{"-", "3"}], " ", "\[Pi]"}], ",", 
       RowBox[{"3", " ", "\[Pi]"}]}], "}"}], ",", 
     RowBox[{"Evaluate", "[", "op", "]"}]}], "]"}]}], 
  ";"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{"z10", "=", 
   RowBox[{"Plot", "[", 
    RowBox[{
     RowBox[{"{", 
      RowBox[{
       FractionBox["\[Omega]", 
        RowBox[{
         SuperscriptBox["\[Omega]", "2"], "+", 
         SuperscriptBox["a", "2"]}]], ",", 
       RowBox[{"Abs", "[", 
        RowBox[{"\[ImaginaryI]", " ", 
         SuperscriptBox["\[ExponentialE]", 
          RowBox[{
           RowBox[{"-", "a"}], " ", "\[Omega]"}]], " ", "\[Pi]", " ", 
         RowBox[{"Sign", "[", 
          RowBox[{"Re", "[", "a", "]"}], "]"}], " ", 
         RowBox[{"(", 
          RowBox[{
           RowBox[{
            SuperscriptBox["\[ExponentialE]", 
             RowBox[{"2", " ", "a", " ", "\[Omega]"}]], " ", 
            RowBox[{"HeavisideTheta", "[", 
             RowBox[{
              RowBox[{"-", "\[Omega]"}], " ", 
              RowBox[{"Sign", "[", 
               RowBox[{"Re", "[", "a", "]"}], "]"}]}], "]"}]}], "-", 
           RowBox[{"HeavisideTheta", "[", 
            RowBox[{"\[Omega]", " ", 
             RowBox[{"Sign", "[", 
              RowBox[{"Re", "[", "a", "]"}], "]"}]}], "]"}]}], ")"}]}], 
        "]"}]}], "}"}], ",", 
     RowBox[{"{", 
      RowBox[{"\[Omega]", ",", 
       RowBox[{
        RowBox[{"-", "3"}], " ", "\[Pi]"}], ",", 
       RowBox[{"3", " ", "\[Pi]"}]}], "}"}], ",", 
     RowBox[{"Evaluate", "[", "op", "]"}]}], "]"}]}], ";"}], "\n", 
 RowBox[{
  RowBox[{"z12", "=", 
   RowBox[{"Plot", "[", 
    RowBox[{
     RowBox[{"{", 
      RowBox[{
       SuperscriptBox["\[ExponentialE]", 
        RowBox[{"-", 
         SuperscriptBox["\[Omega]", "2"]}]], ",", 
       RowBox[{
        SuperscriptBox["\[ExponentialE]", 
         RowBox[{"-", 
          FractionBox[
           SuperscriptBox["\[Omega]", "2"], "4"]}]], " ", 
        SqrtBox["\[Pi]"]}]}], "}"}], ",", 
     RowBox[{"{", 
      RowBox[{"\[Omega]", ",", 
       RowBox[{"-", "\[Pi]"}], ",", "\[Pi]"}], "}"}], ",", 
     RowBox[{"Evaluate", "[", "op", "]"}]}], "]"}]}], ";"}], "\n", 
 RowBox[{"Show", "[", 
  RowBox[{
   RowBox[{"GraphicsGrid", "[", 
    RowBox[{"{", 
     RowBox[{
      RowBox[{"{", 
       RowBox[{"z4", ",", "z6"}], "}"}], ",", 
      RowBox[{"{", 
       RowBox[{"z8", ",", "z9"}], "}"}], ",", 
      RowBox[{"{", 
       RowBox[{"z10", ",", "z12"}], "}"}]}], "}"}], "]"}], ",", 
   RowBox[{"Epilog", "\[Rule]", 
    RowBox[{"{", 
     RowBox[{
      RowBox[{"Text", "[", 
       RowBox[{
        RowBox[{"Style", "[", 
         RowBox[{"\"\<4.\>\"", ",", "15"}], "]"}], ",", 
        RowBox[{"{", 
         RowBox[{"100", ",", 
          RowBox[{"-", "25"}]}], "}"}]}], "]"}], ",", 
      RowBox[{"Text", "[", 
       RowBox[{
        RowBox[{"Style", "[", 
         RowBox[{"\"\<6.\>\"", ",", "15"}], "]"}], ",", 
        RowBox[{"{", 
         RowBox[{"480", ",", 
          RowBox[{"-", "25"}]}], "}"}]}], "]"}], ",", 
      RowBox[{"Text", "[", 
       RowBox[{
        RowBox[{"Style", "[", 
         RowBox[{"\"\<8.\>\"", ",", "15"}], "]"}], ",", 
        RowBox[{"{", 
         RowBox[{"100", ",", 
          RowBox[{"-", "265"}]}], "}"}]}], "]"}], ",", 
      RowBox[{"Text", "[", 
       RowBox[{
        RowBox[{"Style", "[", 
         RowBox[{"\"\<9.\>\"", ",", "15"}], "]"}], ",", 
        RowBox[{"{", 
         RowBox[{"480", ",", 
          RowBox[{"-", "265"}]}], "}"}]}], "]"}], ",", 
      RowBox[{"Text", "[", 
       RowBox[{
        RowBox[{"Style", "[", 
         RowBox[{"\"\<10.\>\"", ",", "15"}], "]"}], ",", 
        RowBox[{"{", 
         RowBox[{"90", ",", 
          RowBox[{"-", "505"}]}], "}"}]}], "]"}], ",", 
      RowBox[{"Text", "[", 
       RowBox[{
        RowBox[{"Style", "[", 
         RowBox[{"\"\<12.\>\"", ",", "15"}], "]"}], ",", 
        RowBox[{"{", 
         RowBox[{"480", ",", 
          RowBox[{"-", "505"}]}], "}"}]}], "]"}]}], "}"}]}]}], 
  "]"}]}], "Input",
 CellChangeTimes->{{3.40955371175566*^9, 3.40955371659966*^9}, {
   3.40955375320166*^9, 3.40955375389366*^9}, {3.40955379993766*^9, 
   3.40955385903266*^9}, {3.40955390265266*^9, 3.40955394218266*^9}, {
   3.4095540003586597`*^9, 3.40955400172466*^9}, {3.40955403586866*^9, 
   3.40955410794466*^9}, {3.40955415349466*^9, 3.40955417954066*^9}, {
   3.40955423215666*^9, 3.4095542955826597`*^9}, {3.4095544236746597`*^9, 
   3.4095545547916603`*^9}, {3.40955469116066*^9, 3.40955469646666*^9}, {
   3.40955472922666*^9, 3.40955474100266*^9}, {3.40955483822666*^9, 
   3.40955484231166*^9}, {3.40955523621566*^9, 3.4095553482656603`*^9}, {
   3.4095553793326597`*^9, 3.40955547058766*^9}, {3.40955552188666*^9, 
   3.40955561971166*^9}, 3.40955575720966*^9, {3.4095557976296597`*^9, 
   3.40955581432766*^9}, {3.4095559618326597`*^9, 3.40955598356266*^9}, {
   3.40955601542066*^9, 3.40955604313966*^9}, 3.4111144457977266`*^9},
 CellLabel->"In[6]:="],

Cell[BoxData[
 GraphicsBox[{{}, {{InsetBox[
      GraphicsBox[{{}, {}, 
        {GrayLevel[0], LineBox[CompressedData["
1:eJwUW3c8le8btiJ773XOCUnItyXCU0ZLKpX2VCJKRakkSmZJ2SOrkshIRinj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          "]]}, 
        {GrayLevel[0], Thickness[0.016], LineBox[CompressedData["
1:eJwUWHk8Vc8bzr6Le+37tSUkKbLPsUSpFClLSCq0kDaVlCWUSF8iQhFFUUiS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          "]]}},
       AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948],
       Axes->True,
       AxesLabel->{
         FormBox["\"t,\[Omega]\"", TraditionalForm], 
         FormBox["\"f(t), F(\[Omega])\"", TraditionalForm]},
       AxesOrigin->{0, 0},
       PlotRange->
        NCache[{{(-3) Pi, 3 Pi}, {-2, 2}}, {{-9.42477796076938, 
          9.42477796076938}, {-2, 2}}],
       PlotRangeClipping->True,
       PlotRangePadding->{
         Scaled[0.02], Automatic}], {192., -119.58957682310464`}, 
      ImageScaled[{0.5, 0.5}], {360., 222.4922359499621}], InsetBox[
      GraphicsBox[{{}, {}, 
        {GrayLevel[0], LineBox[CompressedData["
1:eJxN1n8w1AkUAPDV2fyoPdaKSHYRDsmvUK3b9evay5Vf1VnXlVS6pOLUkU0l
uj0uKcX6cYsbP4tJlEocbdpMknL57bo2ofZwipYVbt3dDO9938ybN5958+bN
++8Z7Qn3D1lEIpEu/Zf/V/ltr8jYHmMRaT5GftpZxe9Ev+JGTF5sQz+eTucV
taCFrL74p/fR7o3Rlxml6OSOwioxD20sU0wuNUBvo7t4l3sbgQMaaeXDKQww
z5Ck1l1EB29NHvpmmmIIfjqmVr8t1QDnHZiNrTJ9cHF1eu3zID1whqNpw9I3
umBBSuPhA5t1wM4SoeVsizY496iwfVkADaw1cM3ET0QFW2yWJYg9NcG/MLK0
bvpTwBG2QrnUUh38s43aXMp6FXD9myzf46rKuP98mvh3ihI4vSuE/GfxzL0F
N+6y8Io/j54cHEkxP4bmyo4uj3RDG1DjrVReTIMLvXL97KjoqrrOnB9PTIEH
PbNfW+5B6zzZad76Jfp470CFvg7aRT7+4HqFHCy21RjqGZwEtxdwnNb4ToBP
8wxn+evQln4T9yUMdJwif0vqmAxsHajYJ7uE5n9663JNxwew3eC5QFo9+kXt
HvqhYrR9qGbZymi05EFYQ9xy9LoY47GNO8bB/T4fb+d5oFPMWmOnrNADbSdV
S2fHwKlreuiUXLQLuWIwhI+W/sEvqz+CZiWtdY5go4f6L3i3vXoPTq/Zr726
Ce2a+nnv2Uq0gDUc4hSPdlvWYHXhIHpkOHPsrT86syH8jisT7ZG18WSWCXo0
fKXH+BK0/XkpVSB9N+/37MQNghzOXbTkrYfFxyR0snue67dW6HU50wH3noyC
narlwdF7pWCHNlmYzXQfWFlvh1kc+RE6X1Y3N9LIXnCX0yLR86jX4BhJRH/t
d1LwikTJ4iLuKPizcDG30uwd2Onrq6V1MvQsJzWIof2evXDvy4GWv/qs0aIz
6scKOOh8Q45iXzD6bG1CotkJ9H6uSEuahra4tN487BFa3SaqcvVr9EjzDebo
DLqCvNr3e5sxsFOMYUy0AO25+5PmhH3jYLN/2Nu/OIVWzY6VLM5EN7dNfEhq
RvtzpAYX7T+Ag9a0HBGSZGDerEDrlnACTCcrsRS30GJKWCjnGVqDzhb1KE2C
C93eHlbsRz/jOzdx7OTgVdTu070Pp7Bvqvf33OgMeEv1XjfHIZLrgjNMdd1L
DJTBOQW7GVeXq4B1swNW5ZHVwVHdli/97CngJtrjDV7amuBNkkN9m65TweY3
e6OoNjQw24NO31qiDfaS+xkfZeuAb9z00d7xmy6YksYMNgrUA+fbKkTBo/rg
9I5zGgcPGIB5uSp3fRcZguvCvf3m4uhgocJRQYtlgLd1Mc9kcIzAzLUlM6fI
xuAVBUkF29vQB0vErCME15TN9fAJ5lb9oFlNsOBh8En9drSWdH2AhGA16yH1
0E7CvJ1p8RmCrzjudssmeCOrM7qZ4LM+DQPWXWhSZHb9OMG+UR2BS7rReTzN
CROCWQl8q+0Ex6ZFZt4h+EnmNYdWglfkSJ9KCa4p2kXW7yHcU5r1qz3B3PJ2
5lcEX7mh0bWX4Pl/CPwvvWFn4w==
          "]]}, 
        {GrayLevel[0], Thickness[0.016], LineBox[CompressedData["
1:eJw1m3k4lN///yWyLzOWrDNDqGwhWUrOCSUqUr2jLC0oEiVRJEqISJsQUVQS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          "]]}},
       AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948],
       Axes->True,
       AxesLabel->{
         FormBox["\"t,\[Omega]\"", TraditionalForm], 
         FormBox["\"f(t), F(\[Omega])\"", TraditionalForm]},
       AxesOrigin->{0, 0},
       PlotRange->
        NCache[{{(-3) Pi, 3 Pi}, {-2, 2}}, {{-9.42477796076938, 
          9.42477796076938}, {-2, 2}}],
       PlotRangeClipping->True,
       PlotRangePadding->{
         Scaled[0.02], Automatic}], {576., -119.58957682310464`}, 
      ImageScaled[{0.5, 0.5}], {360., 222.4922359499621}]}, {InsetBox[
      GraphicsBox[{{}, {}, 
        {GrayLevel[0], LineBox[CompressedData["
1:eJxN1GtIk2EUB/A3cdnM4dyWa3O4i63IME2bZYuZFolmc/PCZlJpIphdFKUZ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          "]]}, 
        {GrayLevel[0], Thickness[0.016], LineBox[CompressedData["
1:eJwU2nk8VN8bB3BrdjFjX2bGXrKEFlI9RwtCaftGodKmBSlRSZFolZBspUUl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