The SCC-100 parallel processor utilizes a fully-programmable, 32-bit MIMD architecture optimized for image and signal processing. Applications include image registration, clutter suppression, velocity filtering, multispectral processing, medical imaging and computer vision research as well as radar and sonar signal processing. The first SCC-100 processor, with 19 nodes and a peak throughput in excess of 1 GFLOPS, was recently delivered. A micro-miniature version using hybrid wafer-scale integration is currently under development for space applications.

In this correspondence we present a new algorithm for computing the correlation [mi][/mi]. For applications where the "cost" of a multiplication is greater than that of an addition, the new algorithm is always more computationally efficient than direct evaluation of the correlation, and it is generally more efficient than FFT methods for processing 128 or fewer data points, or for calculating only the first L values of Rk, for L < 10 log2 2N.

G. E. Albert's general sequential test for making one of r distinct decisions about a distribution functionF(x_{i}|x_{i-1})by observing a sequence ofx_{i}'s is presented, and his results, which give the performance of this test as the solutions of integral equations, are stated. This test is more general than the usual sequential probability ratio test of Wald, and includes nonoptimum, as well as Wald's optimum, sequential tests. Albert's equations are used to treat the incoherent detection of a sine wave in Gaussian noise by a biased square-law detector. This is the detector which uses samplesy_{i}of the envelope of the received waveform to calculate the sumsx_{i} = k \sum_{j=1}^{i} (yj^{2} -bias), i = 1, 2, \cdots, and sequentially compares thex_{i}to two thresholds until anx_{i}is found which is less than the lower thresholdB, or greater than the upper thresholdA. Then ifx_{i} \leq B, it is decided that the signal is not present (dismissal), and ifA \leq x_{i}it is decided that the signal is present (alarm). Though this is not the optimum detector for a sine wave in Gaussian noise (unless the SNR is very small), it is a convenient test to implement and is of considerable interest in its own right. Fory_{i}having the Rayleigh probability distributionf(y) = y \exp\{-y^{2}/2\}, i.e., for the received waveform consisting of Gaussian noise alone, {\em exact} solutions are obtained for the probability of (false) alarm and for the average test duration. These results are unique in that they are valid without restrictions on either the design input SNR or on the thresholds A and B. Curves of the probability of false alarm vs. the upper threshold A, and of the average test duration vs. the expected input SNR are presented, and are compared to similar results of Wald.

In this paper we define a subclass of comma-free codes which has a property called path invariance. The main advantage of codes in this subclass lies in the ease of establishing the positions of the divisions between words. Certain path-invariant comma-free dictionaries usingKsymbols to form n-symbol words are developed and their properties are studied. The number of words in these dictionaries is determined to beL(K-L)^{[n/2]}K^{[(n-1)/2]}whereLis a parameter which equals one whenn \geq 4K/3, and[x]denotes the integral part ofx. That this is the maximum obtainable dictionary size is proved for a special case. The ability of these codes to correct registration (synchronization) errors whennconsecutive symbols are available (as opposed to the2nconsecutive symbols required by general fixed-word-length comma-free codes) is demonstrated. A comparison of dictionary sizes is made for path-invariant comma-free codes, general fixed-word-length comma-free codes, and codes using one symbol as a comma. In the rangeK \leq 6andn \leq 9the path-invariant dictionaries are about\frac{1}{2}to\frac{3}{4}the size of the corresponding general comma-free dictionaries. Asymptotic dictionary sizes are obtained forK \rightarrow \inftyand forn \rightarrow \infty.