University of California

About: University of California is a education organization based out in Oakland, California, United States. It is known for research contribution in the topics: Population & Layer (electronics). The organization has 55175 authors who have published 52933 publications receiving 1491169 citations. The organization is also known as: UC & University of California System.

Incentive and informational properties of preference questions

Abstract: Surveys are frequently used by businesses and governments to elicit information about the public’s preferences. They have become the most common way to gather preference information regarding goods, that are not (or are not yet) bought or sold in markets. In this paper we apply the standard neoclassical economic framework to generate predictions about how rational agents would answer such survey questions, which in turn implies how such survey data should be interpreted. In some situations, the standard economic model would be expected to have no predictive power. For situations where it does have predictive power, we compare different survey formats with respect to: (a) the information that the question itself reveals to the respondent, (b) the strategic incentives the respondent faces in answering the question, and (c) the information revealed by the respondent’s answer.

Finite-sample sizes of johansen's likelihood ratio tests for cointegration

Abstract: This study examines the finite-sample bias of S. Johansen's likelihood ratio tests for cointegration using the Monte Carlo method. Response surface analysis is employed to obtain approximations to the finite-sample critical values and illustrate the individual roles of the sample size, the dimension of the variable system, and the lag order in determining the finite-sample bias of Johansen's tests. The study further shows the importance of lag length selection for Johansen's tests and the performance of standard lag selection criteria in choosing the proper lag length is investigated. Monte Carlo results concerning the sensitivity of Johansen's tests to non-normal innovations are also reported. Copyright 1993 by Blackwell Publishing Ltd

How to generate cryptographically strong sequences of pseudo random bits

Abstract: Much effort has been devoted in the second half of this century to make precise the notion of Randomness. Let us informally recall one of these definitions due to Kolmogorov []. A sequence of bits A =all a2••.•• at is random if the length of the minimal program outputting A is at least k We remark that the above definition is highly non constructive and rules out the possibility of pseudo random number generators. Also. the length of a program, from a Complexity Theory point of view, is a rather unnatural measure. A more operative definition of Randomness should be pursued in the light of modern Complexity Theory.

Differential Equations, Dynamical Systems, and an Introduction to Chaos

Abstract: Hirsch, Devaney, and Smale's classic "Differential Equations, Dynamical Systems, and an Introduction to Chaos" has been used by professors as the primary text for undergraduate and graduate level courses covering differential equations. It provides a theoretical approach to dynamical systems and chaos written for a diverse student population among the fields of mathematics, science, and engineering. Prominent experts provide everything students need to know about dynamical systems as students seek to develop sufficient mathematical skills to analyze the types of differential equations that arise in their area of study. The authors provide rigorous exercises and examples clearly and easily by slowly introducing linear systems of differential equations. Calculus is required as specialized advanced topics not usually found in elementary differential equations courses are included, such as exploring the world of discrete dynamical systems and describing chaotic systems. This is a classic text by three of the world's most prominent mathematicians. It continues the tradition of expository excellence. It contains updated material and expanded applications for use in applied studies.

Resistance Switching Memories Are Memristors

Abstract: All 2-terminal non-volatile memory devices based on resistance switching are memristors, regardless of the device material and physical operating mechanisms. They all exhibit a distinctive “fingerprint” characterized by a pinched hysteresis loop confined to the first and the third quadrants of the v–i plane whose contour shape in general changes with both the amplitude and frequency of any periodic “sine-wave-like” input voltage source, or current source. In particular, the pinched hysteresis loop shrinks and tends to a straight line as frequency increases. Though numerous examples of voltage vs. current pinched hysteresis loops have been published in many unrelated fields, such as biology, chemistry, physics, etc., and observed from many unrelated phenomena, such as gas discharge arcs, mercury lamps, power conversion devices, earthquake conductance variations, etc., we restrict our examples in this tutorial to solid-state and/or nano devices where copious examples of published pinched hysteresis loops abound. In particular, we sampled arbitrarily, one example from each year between the years 2000 and 2010, to demonstrate that the memristor is a device that does not depend on any particular material, or physical mechanism. For example, we have shown that spin-transfer magnetic tunnel junctions are examples of memristors. We have also demonstrated that both bipolar and unipolar resistance switching devices are memristors.