SIM-DSP: A DSP-Enhanced CAD Platform for Signal Integrity Macromodeling and Simulation

Macromodeling-Simulation process for signal integrity verifications has become necessary for the high speed circuit system design. This paper aims to introduce a “VLSI Signal Integrity Macromodeling and Simulation via Digital Signal Processing Techniques” framework (known as SIM-DSP framework), which applies digital signal processing techniques to facilitate the SI verification process in the pre-layout design phase. Core identification modules and peripheral (pre-/post-)processing modules have been developed and assembled to form a verification flow. In particular, a single-step discrete cosine transform truncation (DCTT) module has been developed for modeling-simulation process. In DCTT, the response modeling problem is classified as a signal compression problem, wherein the system response can be represented by a truncated set of non-pole based DCT bases, and error can be analyzed through Parseval’s theorem. Practical examples are given to show the applicability of our proposed framework

Disentangling Intertemporal Substitution and Risk Aversion under the Expected Utility Theorem

A disturbing feature of the conventional objective function for intertemporal decisions under uncertainty is that the agent's attitudes toward intertemporal substitution and risk aversion are entangled. This paper shows that, in contrast to common perception, the two attitudes can be completely disentangled under the expected utility theorem (EUT) by modeling each of them successively in two steps. The conventional form is nested as a special case where the functions describing the two attitudes are identical. The proposed framework requires only the standard axioms of the EUT, in addition to a regulatory assumption. It is flexible in accommodating different combinations of the two attitudes, indifferent to the timing of resolution of uncertainty, intuitive to interpret, and extendable to multiple goods. The objective function under the proposed framework is time inconsistent according to Strotz's (1955) definition. I argue that Strotz's notion of time consistency is misguided. It is constructed based on a priori assumption that the agent should continuously forget history as time progresses. But this means the agent is either chronically amnesiac or self-contradictory. To be truly consistent, the agent should have one and only one objective function, determined at birth, throughout his entire life. As history unfolds, the agent updates his information set, but not his objective function

Disentangling Intertemporal Substitution and Risk Aversion under the Expected Utility Theorem

A disturbing feature of the conventional objective function for intertemporal decisions under uncertainty is that the agent's attitudes toward intertemporal substitution and risk aversion are entangled. This paper shows that, in contrast to common perception, the two attitudes can be completely disentangled under the expected utility theorem (EUT) by modeling each of them successively in two steps. The conventional form is nested as a special case where the functions describing the two attitudes are identical. The proposed framework requires only the standard axioms of the EUT, in addition to a regulatory assumption. It is flexible in accommodating different combinations of the two attitudes, indifferent to the timing of resolution of uncertainty, intuitive to interpret, and extendable to multiple goods. The objective function under the proposed framework is time inconsistent according to Strotz's (1955) definition. I argue that Strotz's notion of time consistency is misguided. It is constructed based on a priori assumption that the agent should continuously forget history as time progresses. But this means the agent is either chronically amnesiac or self-contradictory. To be truly consistent, the agent should have one and only one objective function, determined at birth, throughout his entire life. As history unfolds, the agent updates his information set, but not his objective function.Intertemporal substitution; Risk aversion; Expected utility theorem; Time consistency; Equity premium puzzle

COMPETITIVE DYNAMICS IN ELECTRONIC NETWORKS - ACHIEVING COMPETITIVENESS THROUGH INTERORGANIZATIONAL SYSTEMS

Many dramatic and potentially powerful uses of information technology involveinterorganizational systems (IOS). These systems, defined as distributed computing systems thatsupport shared processes between firms, have become fundamental to business operations,spanning multiple activities in value/supply chains. They have opened avenues to unprecedentedcollaborative linkages between firms. As IOS-mediated relational networks are rapidly evolving,roles of IOS have progressively changed beyond those of efficiency and power functions.To fully appreciate modern roles of IOS in e-business, this dissertation addresses two keyresearch questions: (1) How do firms achieve competitiveness through IOS? (2) How do IOSinfluence competitive behaviors of the competing firms in intertwined electronic networks? Itdoes so by integrating three research streams – social network analysis, interorganizationalsystems, and competitive dynamics – into a model of competitive dynamics in electronicnetworks. This study focuses on the paired relationships between the three constructs of networkstructure, IOS use, and competitive action, and empirically investigates nine general hypotheses.Data collection focuses on second-hand data in the automotive industry. A total of 805collaborative relationships, 106 IOS technologies and applications, and 305 competitive actionsinvolving nine major automakers are collected. Data sources include databases, major tradepublications, Web sites, and industry indices. Data analysis includes network analysis, ANOVAtest, and correlation.Empirical results support the general contention that network structure and IOS use coevolveand influence competitive action. Building on these results, a framework characterizingIOS\u27s roles in achieving firm competitiveness is concluded and advanced. This dissertation broadens our view of IOS\u27s roles in e-business. It contributes to IS/IOS theory, methodology, and practice. First, this study examines IOS-mediated networks inmultiple levels, including firm-level, pair-level, and network-level. It provides new theoreticalconceptualizations of IOS\u27s roles. Second, this study advances a new IT value measureaddressing limitations of the traditional measures. Third, it introduces a novel, usefulmethodology for data collection. Fourth, results from this study can guide a firm\u27s e-businessinitiatives for using IOS as powerful tools for achieving firm competitiveness

Exploiting implicit information from data for linear macromodeling

In macromodeling, data points of sampled structure responses are always matched to construct linear macromodels for transient simulations of packaging structures. However, implicit information from sampled data has not been exploited comprehensively to facilitate the identification process. In this paper, we exploit implicit information from the sampled data for linear marcomodeling. First, in order to include complementary data for a more informative identification, we propose a discrete-time domain identification framework for frequency-/time-/hybrid-domain macromodeling. Second, we introduce pre-/post-processing techniques (e.g., P-norm identification criterion and warped frequency-/hybrid-domain identification) to interpret implicit information for configurations of identifications. Various examples from chip-level to board-level are used to demonstrate the performance of the proposed framework. © 2013 IEEE.published_or_final_versio