3 1.1 Simals averngr stock index) arc ~ v l ~ onumbers lc and so likewise discrete Iri this case bolh the independent arid tbc dependent variables arc: discrcte $ 15 0, Y 10 L- 1.0 1.3 1.7 2.0 2.3 2.7 3.0 3.3 3.7 4.0 4.3 4.7 5.0 mark Figure 1.4:Frequency of e m w d marks for a test in systems theory The signals u7e have ronsidcrcd thus far have been ryiiant,iticas that clcpend on a m q l e irrtlepcdcmt variable how eve^, tliezp arc yuantitics with t~t?i)c?ntlciic.it.s on two or more variables The grcyscalos of Figure 1.5 rlepeird on both thc E and the y co-ordinates Here both axes represent independent variables The dependent variable s(x.y) is entered along one axis, but, is n greyscale value between the extremp values black wid white Wlieii W P adcl mot,iori to pict,ures, wc h:me c2 depcntleiicy on t k r w iiidrpendcrit vruid~les(Pignrtt 1.6): two co-ordinates arid thnc %'c citll these two- 01- thrccdirnenyional (or gcnerallp multidiineiisio~~a1) signals When greyscaln values cliaiige continuously over space or over space and time, these are continuous signals All (mr examples have shown parameters (voltage, Z,miperatiirc, stotk index, frequencies greyscale) that change in rda tion to values of the iridependent variahles 'L'lierc~by thc?y tr;znurnit c*rrtaininformation In this booh we define it signal BS follou\s: L- _I Definition I: Signal -II A signal as a fil,nctaon o r sequence of val,ires th,at represenls ~ri$!orwcutzon _ ding exaxxiples hil\rp shown that, 4gaaJs caii a ~ s i t ~ctifftwnt m iorms Signals can l x c*l:wsifit.d according tJo various rritmia, 1lie inost important o f which %resnmunarimi in Table L.1