IBM

About: IBM is a company organization based out in Armonk, New York, United States. It is known for research contribution in the topics: Layer (electronics) & Cache. The organization has 134567 authors who have published 253905 publications receiving 7458795 citations. The organization is also known as: International Business Machines Corporation & Big Blue.

Virtual pointing device for touchscreens

Abstract: A method, memory, and apparatus, having at least a processor, memory, and touchscreen, for creating a virtual pointing device. The method includes the steps of displaying a non-activated virtual pointing device on the touchscreen, in response to detecting at least one finger placed on the virtual pointing device, activating the virtual pointing device, and moving the virtual pointing device in accordance with movement of the at least one finger.

Algorithmic Information Theory

Abstract: This paper reviews algorithmic information theory, which is an attempt to apply information-theoretic and probabilistic ideas to recursive function theory. Typical concerns in this approach are, for example, the number of bits of information required to specify an algorithm, or the probability that a program whose bits are chosen by coin flipping produces a given output. During the past few years the definitions of algorithmic information theory have been reformulated. The basic features of the new formalism are presented here and certain results of R. M. Solovay are reported.

Reduced-complexity decoding of LDPC codes

Abstract: Various log-likelihood-ratio-based belief-propagation (LLR-BP) decoding algorithms and their reduced-complexity derivatives for low-density parity-check (LDPC) codes are presented. Numerically accurate representations of the check-node update computation used in LLR-BP decoding are described. Furthermore, approximate representations of the decoding computations are shown to achieve a reduction in complexity by simplifying the check-node update, or symbol-node update, or both. In particular, two main approaches for simplified check-node updates are presented that are based on the so-called min-sum approximation coupled with either a normalization term or an additive offset term. Density evolution is used to analyze the performance of these decoding algorithms, to determine the optimum values of the key parameters, and to evaluate finite quantization effects. Simulation results show that these reduced-complexity decoding algorithms for LDPC codes achieve a performance very close to that of the BP algorithm. The unified treatment of decoding techniques for LDPC codes presented here provides flexibility in selecting the appropriate scheme from performance, latency, computational-complexity, and memory-requirement perspectives.

Self-Consistent Results for n -Type Si Inversion Layers

Abstract: Self-consistent results for energy levels, populations, and charge distributions are given for $n$-type inversion layers on $p$-type silicon. Quantum effects are taken into account in the effective-mass approximation, and the envelope wave function is assumed to vanish at the surface. Approximate analytic results are given for some special cases. Numerical results are given for representative surface orientations, bulk acceptor concentrations, inversion-layer electron concentrations, and temperatures.