al line [16]. This "function of royal blood whose distinguished properties set it apart from its bourgeois brethren" [17] is given by where x(n/2W) represents the specified values and x(t) is the cardinal func- tion of the specified values, a function whose Fourier transform is strictly band limited in the frequency domain [15]-[18]. Based on this result, the sam- pling theory used in a communication context by Hartley [19], Nyquist [20], Kotelnikov [21], and Shannon [22] states that a function band limited to The Historical Origins of Spread-Spectrum Communications W Hz can be represented without loss of information by samples spaced 1/(2W) seconds apart. Generalizations [23], [24] of this result indicate that a set of approximately 2TW orthogonal functions of T seconds duration and occupying W Hz can be constructed. In SS theory, this provides the con- nection between the number of possible orthogonal signaling formats and system bandwidth. Although earlier, Nyquist [20] and later Gabor [25] both had argued using Fourier series that 2TW samples should be sufficient to rep- resent a T-second segment of such a band-limited signal, it was Shannon who made full use of this classical tool. Probabilistic modeling of information flow in communication and control systems was the brainchild of the preeminent mathematician Norbert Wiener of the Massachusetts Institute of Technology (M.I.T.). In 1930, Wiener pub- lished his celebrated paper "Generalized Harmonic Analysis" [26] develop- ing the theory of spectral analysis for nonperiodic infinite-duration functions. When World War II began, Wiener was asked by the National Defense Research Committee (NDRC) to produce a theory for the optimal design of servomechanisms. Potential military applications for this theory existed in many gunfire control problems [27]. The resultant work [28], published ini- tially in 1942 as a classified report and often referred to as the "Yellow Peril," laid the groundwork for modern continuous-parameter estimation theory. By 1947, Wiener's fil