Minimum entropy restoration using FPGAs and high-level techniques

One of the greatest perceived barriers to the widespread use of FPGAs in image processing is the difficulty for application specialists of developing algorithms on reconfigurable hardware. Minimum entropy deconvolution (MED) techniques have been shown to be effective in the restoration of star-field images. This paper reports on an attempt to implement a MED algorithm using simulated annealing, first on a microprocessor, then on an FPGA. The FPGA implementation uses DIME-C, a C-to-gates compiler, coupled with a low-level core library to simplify the design task. Analysis of the C code and output from the DIME-C compiler guided the code optimisation. The paper reports on the design effort that this entailed and the resultant performance improvements

Restoration of star-field images using high-level languages and core libraries

Research into the use of FPGAs in Image Processing began in earnest at the beginning of the 1990s. Since then, many thousands of publications have pointed to the computational capabilities of FPGAs. During this time, FPGAs have seen the application space to which they are applicable grow in tandem with their logic densities. When investigating a particular application, researchers compare FPGAs with alternative technologies such as Digital Signal Processors (DSPs), Application-Specific Integrated Cir-cuits (ASICs), microprocessors and vector processors. The metrics for comparison depend on the needs of the application, and include such measurements as: raw performance, power consumption, unit cost, board footprint, non-recurring engineering cost, design time and design cost. The key metrics for a par-ticular application may also include ratios of these metrics, e.g. power/performance, or performance/unit cost. The work detailed in this paper compares a 90nm-process commodity microprocessor with a plat-form based around a 90nm-process FPGA, focussing on design time and raw performance. The application chosen for implementation was a minimum entropy restoration of star-field images (see [1] for an introduction), with simulated annealing used to converge towards the globally-optimum solution. This application was not chosen in the belief that it would particularly suit one technology over another, but was instead selected as being representative of a computationally intense image-processing application

Financing Constraints and Corporate Investment

Most empirical models of investment rely on the assumption that firms are able to respond to prices set in centralized securities markets (through the "cost of capital" or "q"). An alternative approach emphasizes the importance of cash flow as a determinant of investment spending, because of a "financing hierarchy," in which internal finance has important cost advantages over external finance. We build on recent research concerning imperfections in markets for equity and debt. This work suggests that some firms do not have sufficient access to external capital markets to enable them to respond to changes in the cost of capital, asset prices, or tax-based investment incentives. To the extent that firms are constrained in their ability to raise funds externally, investment spending may be sensitive to the availability of internal finance. That is, investment may display "excess sensitivity" to movements in cash flow. In this paper, we work within the q theory of investment, and examine the importance of a financing hierarchy created by capital-market imperfections. Using panel data on individual manufacturing firms, we compare the investment behavior of rapidly growing firms that exhaust all of their internal finance with that of mature firms paying dividends. We find that q values remain very high for significant periods of time for firms paying no dividends, relative to those for mature firms. We also find that investment is more sensitive to cash flow for the group of firms that our model implies is most likely to face external finance constraints. These results are consistent with the augmented model we propose, which takes into account different financing regimes for different groups of firms. Some extensions and implications for public policy are discussed at the end.

Market Structure and Cyclical Fluctuations in U.S. Manufacturing

The relevance of imperfect competition for models of aggregate economic fluctuations has received increased attention from researchers in both macroeconomics and industrial organization. Measuring properly the size of industry markups of price over marginal cost is important both for assessing the role of market structure and for determining the extent to which excess capacity is a significant feature accompanying imperfect competition in American industry. Using a panel data set on four-digit Census manufacturing industries, this paper expands recent work by Robert Hall on the importance of market structure for understanding cyclical fluctuations. We outline a methodology for estimating industry markups of price over cost and the influence of market structure on cyclical movements in total factor productivity. While we find evidence to support the proposition that price exceeds marginal cost in U.S. manufacturing, our results offer only limited support for the notion that markups are importantly related to differences in industry concentration, though the effect of unionization is important. Concentration effects are important only in industries producing durable goods or differentiated consumer goods. In addition, much of the estimated markup of price over marginal cost is accounted for by fixed costs related to overhead labor, advertising, and central office expenses; we do not find compelling evidence of substantial evidence of excess capacity in most industries.

PRODUCT COMPLEMENTARITY IN PRODUCTION: THE BY-PRODUCT CASE

Production Economics,

Optimal Strategies for Sinusoidal Signal Detection

We derive and study optimal and nearly-optimal strategies for the detection of sinusoidal signals hidden in additive (Gaussian and non-Gaussian) noise. Such strategies are an essential part of algorithms for the detection of the gravitational Continuous Wave (CW) signals produced by pulsars. Optimal strategies are derived for the case where the signal phase is not known and the product of the signal frequency and the observation time is non-integral.Comment: 18 pages, REVTEX4, 7 figures, 2 table

Business Cycles and Oligopoly Supergames: Some Empirical Evidence on Prices and Margins

There has been a significant interest on a theoretical level in the application of supergames to oligopoly behavior. Implications for pricing behavior in trigger-strategy models in response to aggregate demand are of particular importance for public policy considerations. We contrast the predictions for the movements of industry prices over the business cycle of two such models -- put forth by Edward Green and Robert Porter and by Julio Rotemberg and Garth Saloner -- and test the predictions using a panel data set of U.S. manufacturing industries. Our principal findings are four. First, the levels of price-cost margins of concentrated, homogeneous-goods industries, while higher than those of unconcentrated counterparts, appear to be closer to those predicted by a single-period Cournot-Nash equilibrium than monopoly. Second, there is little evidence to support the idea that price-cost margins of these industries have different cyclical patterns from other industries apart from effects by level of industry concentration. Maximum price declines for concentrated industries give little support for the occurrence of price wars during either recessions or booms. Finally, consistent with the predictions of the Rotemberg-Saloner model, the industries with high price-cost margins have more countercyclical price movements than those exhibited by other industries. That gradual price adjustment is quantitatively important for those industries, suggests, however, that other factors may lie behind the apparent rigidity of prices.

Financing Constraints and Corporate Investment

macroeconomics, Financing Constraints, Corporate Investment

Financing Constraints and Corporate Investment: Response to Kaplan and Zingales

Kaplan and Zingales (1995, hereafter KZ) criticize Fazzari, Hubbard and Petersen (1988, hereafter FHP) and much ensuing research that uses cross-sectional differences in firm behavior to test for financing constraints on investment. This reply identifies flaws in the KZ analysis. The questions KZ raise have been considered extensively and rigorously in the literature (most of which is not addressed in KZ), with results broadly similar to those of FHP. We also challenge both of KZ's main results. First, their finding that most of the FHP firms are not financially constrained relies on an inappropriate operational definition of what it means to be constrained. Their definition ignores the incentives for firms that operate in imperfect capital markets to accumulate stocks of cash or maintain unused debt capacity to offset partially shocks to the flow of internal finance. Second, the KZ regression results (lower sensitivity of investment to cash flow for firms classified as constrained than for those classified as unconstrained) are uninformative. Their classification approach relies on possibly self- serving managerial statements that may present a distorted picture of firm's availability of finance. It also employs misleading criteria to make unrealistically fine distinctions in the degree of financing constraints, and emphasizes financial distress rather than financing constraints. Finally, econometric problems affect the interpretation of the KZ regressions. We conclude that the KZ findings do not contradict the interpretation of the empirical results in FHP and subsequent research.