With the increase in the complexity of digital VLSI circuit design, logic design errors can occur during synthesis. In this work, we present a test vector simulation based approach for multiple design error diagnosis and correction. Diagnosis is performed through an implicit enumeration of the erroneous lines in an effort to avoid the exponential explosion of the error space as the number of er...

In this paper we present a novel classifier which integrates a multilayer perceptron and a error-correcting decoder. There are two stages in the classifier, in the first stage, mapping feature vectors from feature space to code space is achieved by a multilayer perceptron; in the second stage, error correcting decoding is done on code space, by which the index of the noisy codeword can be obtai...

This paper analyzes the transmission mechanisms of a contractionary monetary policy shock on the real economy. The sufficiently long regime uniform time period since the political transformation in the Czech Republic provides evidence for effective inflation targeting by the Czech National Bank. I apply a recursive vector autoregression (VAR), a structural VAR, and structural vector error corre...

We examine the statistical power of fundamental and behavioral factors with regards to stock returns of the Dow Jones Industrials Index. With a novel sentiment dataset from over 3.6 million Reuters news articles, we nd signi cant correlations between Reuters sentiment and stock returns. We show with vector autoregression and error correction models that sentiment can explain and predict changes...

In this paper, we describe the use of lexical and semantic features for topic classification in dictated medical reports. First, we employ SVM classification to assign whole reports to coarse work-type categories. Afterwards, text segments and their topic are identified in the output of automatic speech recognition. This is done by assigning work-type-specific topic labels to each word based on...

We examine the explanatory and predictive power of fundamental macroeconomic and behavioral factors with regards to stock returns of the Dow Jones Industrials Index. With a novel sentiment dataset from over 3.6 million Reuters news articles, we nd signi cant correlations between Reuters sentiment and stock returns. We show with vector autoregression and error correction models that Reuters sent...

In this paper, the demand for real money M1, M2 and M3 is estimated for Austria. The modelling takes place within the framework of a small vector autoregression. To estimate the demand for money, two-equation error-correction models are constructed, which contain the short-run dynamics and the long-run economic equilibrium. It is found that a stable money demand exists for all monetary aggregat...

We propose Time-Space Threshold Vector Error Correction (TS-TVEC) model for short term traffic state prediction. The theory of cointegration with error correction mechanism is employed in the general design of the new model TS-TVEC. An inherent connection between mathematical form of error correction model and the microscopic traffic flow theory is revealed through the transformation of the Fun...

In area efficient low error compensation multiplier design is using fixed width RPR(Reduced Precision Redundancy). We propose a new method called fixed width RPR for DSP applications. This fixed width multiplier is placed in ANT architecture to meet high speed, low power consumption and area efficiency. The fixed RPR is designed with compensation circuit for minimizing the occurrence of error. ...