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Two-dimensional windows find applications in many diverse fields, such as the spectral estimation of random fields, the design of two-dimensional digital filters, optical apodization, and antenna array design. Many good one- dimensional windows have been devised, but relatively few two-dimensional windows have been investigated. In this paper we show that good two-dimensional windows can be obtained by rotating good one-dimensional windows. That is, if w(x) is a good symmetrical one-dimensional window, then w sub 2(x,y) = w(square root of (x squared + y squared)) is a good circularly symmetrical two- dimensional window.

The paper discusses some aspects of the stability problem in two- dimensional recursive filtering. In particular, the author derives a simplified version of a stability theorem due to Shanks and shows that it is equivalent to some results of Ansell. The paper also gives several examples of stability tests and poses a few unsolved problems.

Data compression, in the paper, is used to denote the reducing of an input data set prior to transmission, as opposed to data reduction, the analytical processing of the set upon reception. Source encoding techniques are classified into sampling and analog to digital conversion, codebook techniques, predictive subtractive coding and delta modulation, along with aperature and partitioning techniques. Some of the most recent work discussed includes adaptive predictive coding, picture bandwidth compression-source coding, and a techniques for subjective performance measures. The paper concludes with an information theoretic approach to data compression. (Author), Prepared in cooperation with University of Southern California, Los Angeles, Massachusetts Inst. of Tech., Cambridge and Bell Telephone Labs., Murray Hill, NJ.