In all System-on-a-Chip (SoC) designs, there is a necessity to reduce the large test data volume and this is achieved by test data compression. One of the methods is the variable-to-variable length compression method. A selective run-length based compression which comes under variable-to-variable method is presented in this paper. The proposed work is based on threshold calculation on don’t car...

The purpose of the present study was to examine the validity of using a 20 m progressive shuttle run test to estimate maximal oxygen uptake. Running ability was described as the final level attained on the shuttle run test and as time on a 5 km run. Maximal oxygen uptake (VO2 max) was determined directly for seventy-four volunteers (36 men, 38 women) who also completed the shuttle run test. Max...

We consider the problem of packing fixed-length patterns into a permutation, and develop a connection between the number of large patterns and the number of bonds in a permutation. Improving upon a result of Kaplansky and Wolfowitz, we obtain exact values for the expectation and variance for the number of large patterns in a random permutation. Finally, we are able to generalize the idea of bon...

For any memoryless communication channel with a binary-valued input and a one-dimensional real-valued output, we introduce a probabilistic lower bound on the mutual information given empirical observations on the channel. The bound is built on the Dvoretzky-Kiefer-Wolfowitz inequality and is distribution free. A quadratic time algorithm is described for computing the bound and its corresponding...

In [1] we determined the capacity region of the multiple–access channel (MAC) by proving a coding theorem and its weak converse. Recently Dueck [2] proved a strong converse theorem in the sense of Wolfowitz [3]. His proof uses the Ahlswede–Gács–Körner [4] method of “blowing up decoding sets” in conjunction with a new “wringing technique”. This technique makes it now possible to prove strong con...

Weighted averages of Kiefer–Wolfowitz-type procedures, which are driven by larger step lengths than usual, can achieve the optimal rate of convergence. A priori knowledge of a lower bound on the smallest eigenvalue of the Hessian matrix is avoided. The asymptotic mean squared error of the weighted averaging algorithm is the same as would emerge using a Newton-type adaptive algorithm. Several di...

Various papers have analyzed the noisy optimization of convex functions. This analysis has been made according to several criteria used to evaluate the performance of algorithms: uniform rate, simple regret and cumulative regret. We propose an iterative optimization framework, a particular instance of which, using Hessian approximations, provably (i) reaches the same rate as Kiefer-Wolfowitz al...