We describe a new method for design error diagnosis in digital circuits, that doesn’t use any error model. A diagnostic specific pre-analysis of the circuit extracts a subcircuit suspected to be erroneous. Contrary to other published works, here the necessary re-synthesis of the subcircuit need not be applied to the whole function of an internal signal in terms of primary inputs, but may stop a...

We show that a simple function has small unbounded error communication complexity in the k-party number-on-forehead (NOF) model but every probabilistic protocol that solves it with sub-exponential advantage over random guessing has cost essentially Ω (√ n 4 ) bits. Such a separation was first shown for k = 2 independently by Buhrman et al. [8] and Sherstov [24]. A very recent work of Sherstov [...

Bayesian information geometry provides a general error decomposition theorem for arbitrary statistical models and a family of information deviations that include Kullback-Leibler information as a special case. When applied to Gaussian measures it takes the classical Hilbert space (Sobolev space) theories for estimation (regression, filtering, approximation, smoothing) as a special case. When th...

Operational forecasting is hampered both by the rapid divergence of nearby initial conditions and by error in the underlying model. Interest in chaos has fuelled much work on the first of these two issues; this paper focuses on the second. A new approach to quantifying state-dependent model error, the local model drift, is derived and deployed both in examples and in operational numerical weath...

precipitation is considered as one of the most important factures in water cycle. prediction of monthly precipitation is important for many purposes such as estimating torrent, drought, run-off, sediment, irrigation programming and also management of drainage basins.in this study we studied and evaluated gene expression programming to predict the precipitation of the kakareza river (in lorestan...

This paper investigates the nature of model error in complex deterministic nonlinear systems, such as weather forecasting models. Forecasting systems incorporate two components, a forecast model and a data assimilation method. The latter projects a collection of observations of reality into a model state. Key features of model error can be understood in terms of geometric properties of the data...

This paper uses the semiparametric error correction model (Li andWooldridge, 2002) and investigates the dynamics of wage, employment and labor efficiency after introducing five-day work week to the Korean labor market. Efficient working hour function is obtained by nonparametric method (polynomial approximation) and the dynamics are investigated using impulse response analysis. Average derivati...