Interface personalization can improve a user's performance and subjective impression of interface quality and responsiveness. Personalization is difficult to implement as it requires an accurate model of a user's intentions and a formal model of how an interface meets a user's need. We present a novel model for tractable inference of consumer intentions in the context of grocery shopping. The model makes unique use of a priori temporal relations to simplify inference. We then present a simple interface generation framework that was inspired by viewing user interface interaction as a channel coding problem. The resulting model defines a simplified but clear notion of a user's utility for an interface. We demonstrate the effectiveness of the research prototype on some simple data, and explain how the model can be augmented with richer user modeling to create a deployable application.

Through an orthonormal Laguerre expansion, expressions are derived for a lesser known Rician probability distribution-the probability density function (PDF) of the envelope of two fixed-amplitude randomly phased sine waves in narrowband Gaussian noise-and for the integral of the density, the cumulative distribution function (CDF). The principal formula derived has been checked analytically, numerically, and (approximately) graphically. Analytically, the moment-generating function for the PDF of the square of the envelope has been found to be a three-term product of elementary functions times an I/sub 0/ Bessel function (and thus to be in closed form); in confirmation, the same result has been secured via another, more direct route.>

This sequel to R. A. Scholtz's monograph of May 1982, in this TRANSACTIONS, adds to the early history of spread-spectrum communications from circa 1900 until about 15 years ago. Relevant to the origins of this field of radio signaling, the following are included in a number of items of quite recent appreciation: the 1930 invention of secret communications featuring spectrum despreading via a locally generated reference at the receiver; a stratagem of electronic warfare during the Battle of the Bulge, in World War II, that cleverly made use of Armstrong's frequency modulation; and the role of a star actress from the motion picture field, in origination of frequency hopping for antijamming radio control of missiles. Some further, and first-hand, reminiscences are given of germinal M.I.T. spread-spectrum contributions, and of similar noise-correlation radar art. Extensive footnotes cast sidelights on the beginnings of information theory, and also, among other things, on the keeping of military high-technology secrets over decades, even between securitycleared family members. A variety of references is appended.

Augmenting Woodward's total-volume invariance, new information on ambiguity-function behavior is obtained and illustrated by example. The results are of two types, the first dealing with the time4requency volume distribution and providing lower bounds to local volume, and upper bounds to attainable "clear area"; these follow from Parseval's theorem as applied to Siebert's self-transform property. The second category of necessary conditions consists of a set of upper bounds on the norms of the ambiguity function, which places restrictions on the height distribution of the ambiguity surface. As a corollary, it is demonstrated that not all nonnegative functions that are serf-transformable can be ambiguity functions.

Description and performance are given for two slightly different forms of an adaptive receiver that is used with binary signaling in a multichannel communication system. Each channel has a non-dispersive, nonfading propagation path and additive white gaussian noise that is independent of, and equal in intensity to, the other channel noises. Either phase-independent orthogonal signaling (such as FSK) or phase-reversal-comparison signaling is employed to convey to the receiver both the message and information about the path strengths and phases. The receiver measures the path parameters and applies the results to the detection processing as though they were perfectly accurate; it is shown that this procedure is a natural extension of non-adaptive reception. Results are given without derivation for the probability of binary decision error, which depends on the type of signaling, the ratio of the total noise-exclusive signaling energy received to the noise intensity, the number of channels, and the ratio of the effective measurement time to the binary signal duration. The distribution of the received signaling energy among the channels is immaterial. Graphs of error probability are presented for selected system parameters. A novel by-product of the study is an error-probability expression for non-adaptive multichannel reception of quite general binary signaling. Optimal adjustment of the adaptive receiver for fading-path situations is also considered, but corresponding error probabilities have not yet been derived.

A loss of signal detectability results from ideal symmetric limiting of a very narrow-band signal in narrow-band Gaussian noise. At small input snr this loss can be expressed in terms of the degradation of the effective signal energy-to-noise power per cycle ratio. Proceeding from results derived previously by Davenport and Price, an expression is derived for this degradation in terms of the autocorrelation function of the input noise. The degradation is evaluated for three typical input noise autocorrelation functions and is found to be quite small in all these cases. It is seen that the degradation can be made to vanish by appropriately shaping the spectrum of the input noise. Regulation of the input noise spectrum to obtain conditions of limiter operation assumed in this paper may often prove to be a convenient method for reducing loss of signal detectability in band-pass limiters.

If and only if the inputs to a set of nonlinear, zero-memory devices are variates drawn from a Gaussian random process, a useful general relationship may be found between certain input and output statistics of the set. This relationship equates partial derivatives of the (high-order) output correlation coefficient taken with respect to the input correlation coefficients, to the output correlation coefficient of a new set of nonlinear devices bearing a simple derivative relation to the original set. Application is made to the interesting special cases of conventional cross-correlation and autocorrelation functions, and Bussgang's theorem is easily proved. As examples, the output autocorrelation functions are simply obtained for a hard limiter, linear detector, clipper, and smooth limiter.

Solutions are obtained in open form for the optimum, probability-computing detector of either Gaussian signals, or known signals transmitted via scatter-paths, where the signals have been further perturbed by additive white Gaussian noise. The optimum receiver operates on the received waveforms with filter-functions and biasing constants determined by pairs of inhomogeneous and homogeneous integral equations, respectively. General solution in closed form has not been obtained, but it is possible to draw a few broad conclusions, among them that the filter-functions can be physically realizable. Approximate solution (for the optimum scatter-path receiver) at small signal-to-noise ratios yields a block diagram having interesting implications. For a single-scatter-path, the optimum receiver may be interpreted as the combination of a correlator with an optimum estimator of the Wiener type. Certain special cases in which complete solution is possible have been investigated in detail, and appropriate curves are presented. The role and performance of the probability-computing detector in an optimum decision-making receiver, for the types of channels considered, is deferred to a companion paper.

The autocorrelation function and power spectrum of the phase-modulated portion of narrow-band gaussian noise is studied and specific computations are carried out for the case of a rectangular noise spectrum. Related results are given for the noise envelope. General asymptotic expressions for the spectra are obtained, together with experimental verification.