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IPS355 Georg Lindgren
            theory with the different applications. Many are those who have witnessed
            about  his  kindness  and  helpfulness,  to  young  PhD  students  as  well  as  to
            established researchers.

           3.  An overview of his work
               Steve Rice published sixty-four scientific papers during his career. In the
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            list they are categorized into three groups according to focus: Computation,
            mathematics,  and  statistics;  Physics  and  communication  systems;  Signal
            processing.
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               “Mathematical analysis of random noise”, with its 162 pages, belongs to
            all three categories. Its significance for radio  communication and general
            signal processing is obvious – it was written for engineers in an engineering
            environment. Rice was quite familiar with the work by Norbert Wiener on
            correlation functions, harmonic analysis, and filtering of certain “random”
            functions, written as mathematics with electrical engineering applications in
            mind. Rice embraced explicitly the idea of a “stationary stochastic process”
            as  an ensemble of  functions with a  statistical distribution in the sense of
            Khintchine  and  Cramer.  Wiener,  as  prestigious  mathematician,  helped  to
            advocate the statistical´ viewpoint, when he claimed that information is not
            only what has been said, but also what might have been said. It has been
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            argued that Rice’s “Random noise”, Shannon’s “Information theory”, and
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            Wiener’s book on smoothing and prediction, are the three most important
            publications  from  USA  during  the  1940s  to  establish  the  statistical  radio
            communication theory.
               “Mathematical analysis of random noise” has four main parts: (I) on shot
            noise, (II) on power spectra and correlation, (III) on the statistical properties
            of correlated noise, (IV) on non-linear filters. Part
            (II)  presented  a  stationary  process  as  a  random  Fourier  sum,  with  discrete
            spectrum,

                     () = ∑  cos   +  sin   = ∑  cos(  −  ),                 (1)
                                             
                                 
                                       
                                                                   
                                                                         
                                                   
                                                            
                                                       

            with random ( ,  ) and ( ,  ). In part (III) the discrete spectrum is replaced
                                          
                                       
                           
                              
            by a continuous one and the signal () assumed to be Gaussian.
               It took only a decade before the statistical content of parts (I, II, IV) was
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            included in advanced textbooks for radio engineers. But what makes Rice’s
            random  noise  paper  important  for  statistics  research  is  part  (III),  and  the
            statistics  community  was  slow  to  recognize  its  challenges,  namely  the
            statistical  properties  of  the  number  and  location  of  level  crossings  by  a
            stationary process. We will deal with some of these challenges later in this
            paper.
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