Question for covariance stationary process












0












$begingroup$


Given a random variable Y with characteristic function
C(w) = E[exp(iwy)] . Let the random process X(t) be defined as X(t)=cos(wt+y). Show that the process X(t) is covariance stationary if C(1)-C(2)=0.
I have tried expanding the characteristic function in the trigonometric form and using the result to prove stationarity but I'm still unable to solve it. Any hint will be helpful.










share|cite|improve this question









$endgroup$

















    0












    $begingroup$


    Given a random variable Y with characteristic function
    C(w) = E[exp(iwy)] . Let the random process X(t) be defined as X(t)=cos(wt+y). Show that the process X(t) is covariance stationary if C(1)-C(2)=0.
    I have tried expanding the characteristic function in the trigonometric form and using the result to prove stationarity but I'm still unable to solve it. Any hint will be helpful.










    share|cite|improve this question









    $endgroup$















      0












      0








      0





      $begingroup$


      Given a random variable Y with characteristic function
      C(w) = E[exp(iwy)] . Let the random process X(t) be defined as X(t)=cos(wt+y). Show that the process X(t) is covariance stationary if C(1)-C(2)=0.
      I have tried expanding the characteristic function in the trigonometric form and using the result to prove stationarity but I'm still unable to solve it. Any hint will be helpful.










      share|cite|improve this question









      $endgroup$




      Given a random variable Y with characteristic function
      C(w) = E[exp(iwy)] . Let the random process X(t) be defined as X(t)=cos(wt+y). Show that the process X(t) is covariance stationary if C(1)-C(2)=0.
      I have tried expanding the characteristic function in the trigonometric form and using the result to prove stationarity but I'm still unable to solve it. Any hint will be helpful.







      stochastic-processes covariance stationary-processes






      share|cite|improve this question













      share|cite|improve this question











      share|cite|improve this question




      share|cite|improve this question










      asked Jan 12 at 18:57









      Kc17Kc17

      346




      346






















          1 Answer
          1






          active

          oldest

          votes


















          1












          $begingroup$

          Hint



          $$E[X(t)]{=E[cos(wt+y)]\=Eleft[{e^{iwt+iy}+e^{-iwt-iy}over 2}right]\=text{const}}$$and$$E[X(t_1)X(t_2)]{=E[cos(wt_2+y)cos(wt_1+y)]\={1over 2}E[cos(w(t_2-t_1))]\+{1over2}E[cos (wt_1+wt_2+2y)]}$$since $E[X(t_1)X(t_2)]$ must be a function of $t_1-t_2$ so $E[cos (wt_1+wt_2+2y)]=0$. The rest is easy.






          share|cite|improve this answer









          $endgroup$













            Your Answer





            StackExchange.ifUsing("editor", function () {
            return StackExchange.using("mathjaxEditing", function () {
            StackExchange.MarkdownEditor.creationCallbacks.add(function (editor, postfix) {
            StackExchange.mathjaxEditing.prepareWmdForMathJax(editor, postfix, [["$", "$"], ["\\(","\\)"]]);
            });
            });
            }, "mathjax-editing");

            StackExchange.ready(function() {
            var channelOptions = {
            tags: "".split(" "),
            id: "69"
            };
            initTagRenderer("".split(" "), "".split(" "), channelOptions);

            StackExchange.using("externalEditor", function() {
            // Have to fire editor after snippets, if snippets enabled
            if (StackExchange.settings.snippets.snippetsEnabled) {
            StackExchange.using("snippets", function() {
            createEditor();
            });
            }
            else {
            createEditor();
            }
            });

            function createEditor() {
            StackExchange.prepareEditor({
            heartbeatType: 'answer',
            autoActivateHeartbeat: false,
            convertImagesToLinks: true,
            noModals: true,
            showLowRepImageUploadWarning: true,
            reputationToPostImages: 10,
            bindNavPrevention: true,
            postfix: "",
            imageUploader: {
            brandingHtml: "Powered by u003ca class="icon-imgur-white" href="https://imgur.com/"u003eu003c/au003e",
            contentPolicyHtml: "User contributions licensed under u003ca href="https://creativecommons.org/licenses/by-sa/3.0/"u003ecc by-sa 3.0 with attribution requiredu003c/au003e u003ca href="https://stackoverflow.com/legal/content-policy"u003e(content policy)u003c/au003e",
            allowUrls: true
            },
            noCode: true, onDemand: true,
            discardSelector: ".discard-answer"
            ,immediatelyShowMarkdownHelp:true
            });


            }
            });














            draft saved

            draft discarded


















            StackExchange.ready(
            function () {
            StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fmath.stackexchange.com%2fquestions%2f3071252%2fquestion-for-covariance-stationary-process%23new-answer', 'question_page');
            }
            );

            Post as a guest















            Required, but never shown

























            1 Answer
            1






            active

            oldest

            votes








            1 Answer
            1






            active

            oldest

            votes









            active

            oldest

            votes






            active

            oldest

            votes









            1












            $begingroup$

            Hint



            $$E[X(t)]{=E[cos(wt+y)]\=Eleft[{e^{iwt+iy}+e^{-iwt-iy}over 2}right]\=text{const}}$$and$$E[X(t_1)X(t_2)]{=E[cos(wt_2+y)cos(wt_1+y)]\={1over 2}E[cos(w(t_2-t_1))]\+{1over2}E[cos (wt_1+wt_2+2y)]}$$since $E[X(t_1)X(t_2)]$ must be a function of $t_1-t_2$ so $E[cos (wt_1+wt_2+2y)]=0$. The rest is easy.






            share|cite|improve this answer









            $endgroup$


















              1












              $begingroup$

              Hint



              $$E[X(t)]{=E[cos(wt+y)]\=Eleft[{e^{iwt+iy}+e^{-iwt-iy}over 2}right]\=text{const}}$$and$$E[X(t_1)X(t_2)]{=E[cos(wt_2+y)cos(wt_1+y)]\={1over 2}E[cos(w(t_2-t_1))]\+{1over2}E[cos (wt_1+wt_2+2y)]}$$since $E[X(t_1)X(t_2)]$ must be a function of $t_1-t_2$ so $E[cos (wt_1+wt_2+2y)]=0$. The rest is easy.






              share|cite|improve this answer









              $endgroup$
















                1












                1








                1





                $begingroup$

                Hint



                $$E[X(t)]{=E[cos(wt+y)]\=Eleft[{e^{iwt+iy}+e^{-iwt-iy}over 2}right]\=text{const}}$$and$$E[X(t_1)X(t_2)]{=E[cos(wt_2+y)cos(wt_1+y)]\={1over 2}E[cos(w(t_2-t_1))]\+{1over2}E[cos (wt_1+wt_2+2y)]}$$since $E[X(t_1)X(t_2)]$ must be a function of $t_1-t_2$ so $E[cos (wt_1+wt_2+2y)]=0$. The rest is easy.






                share|cite|improve this answer









                $endgroup$



                Hint



                $$E[X(t)]{=E[cos(wt+y)]\=Eleft[{e^{iwt+iy}+e^{-iwt-iy}over 2}right]\=text{const}}$$and$$E[X(t_1)X(t_2)]{=E[cos(wt_2+y)cos(wt_1+y)]\={1over 2}E[cos(w(t_2-t_1))]\+{1over2}E[cos (wt_1+wt_2+2y)]}$$since $E[X(t_1)X(t_2)]$ must be a function of $t_1-t_2$ so $E[cos (wt_1+wt_2+2y)]=0$. The rest is easy.







                share|cite|improve this answer












                share|cite|improve this answer



                share|cite|improve this answer










                answered Jan 12 at 19:07









                Mostafa AyazMostafa Ayaz

                15.3k3939




                15.3k3939






























                    draft saved

                    draft discarded




















































                    Thanks for contributing an answer to Mathematics Stack Exchange!


                    • Please be sure to answer the question. Provide details and share your research!

                    But avoid



                    • Asking for help, clarification, or responding to other answers.

                    • Making statements based on opinion; back them up with references or personal experience.


                    Use MathJax to format equations. MathJax reference.


                    To learn more, see our tips on writing great answers.




                    draft saved


                    draft discarded














                    StackExchange.ready(
                    function () {
                    StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fmath.stackexchange.com%2fquestions%2f3071252%2fquestion-for-covariance-stationary-process%23new-answer', 'question_page');
                    }
                    );

                    Post as a guest















                    Required, but never shown





















































                    Required, but never shown














                    Required, but never shown












                    Required, but never shown







                    Required, but never shown

































                    Required, but never shown














                    Required, but never shown












                    Required, but never shown







                    Required, but never shown







                    Popular posts from this blog

                    Mario Kart Wii

                    What does “Dominus providebit” mean?

                    The Binding of Isaac: Rebirth/Afterbirth