Data sparseness is one of the factors that degrade statistical machine translation (SMT). Existing work has shown that using morphosyntactic information is an effective solution to data sparseness. However, fewer efforts have been made for Chinese-to-English SMT with using English morpho-syntactic analysis. We found that while English is a language with less inﬂection, using English lemmas in training can signiﬁcantly improve the quality of word alignment that leads to yield better translation performance. ...
Suitable for a one- or two-semester undergraduate-level electrical engineering, computer engineering, and computer science course in Discrete Systems and Digital Signal Processing. Assumes some prior knowledge of advanced calculus, linear systems for continuous-time signals, and Fourier series and transforms. Giving students a sound balance of theory and practical application, this no-nonsense text presents the fundamental concepts and techniques of modern digital signal processing with related algorithms and applications.
Some people distinguish between savings and investments, where savings are
monies placed in relatively risk-free accounts with modest rewards, and where
investments involve more risk and the potential for greater rewards. In this
book we do not distinguish between these ideas. We treat them both under
the umbrella of investing.
Computers are one of the most important tools in any field of science and
especially in physics. A student in an undergraduate lab will appreciate the
help of a computer in calculating a result from a series of measurements.
The more advanced researcher will use them for tasks like simulating an
experiment, or solving complex systems of equations. Physics is deeply
connected to mathematics and requires a lot of calculational skills. If one is
only interested in a conceptual understanding of the field, or an estimate of
the outcome of an experiment, simple calculus will probably suffice.
This paper analyzes the stability of linear, lumped, quadratic, and cubic spatial interpolation functions in finite element one‐dimensional kinematic wave schemes for simulation of rainfall‐runoff processes. Galerkin’s residual method transforms the kinematic wave partial
In this paper the spline approximation was applied to the empirical vertical profiles of oceanographic parameters such as temperature, salinity or density to obtain a more precise and reliable result of interpolation. Our experiments with the case of observed temperature profiles in Eastern Sea show that the cubic polynomial spline method has a higher reliability and precision in a comparison with the linear interpolation and other traditional methods. The method was realized as a subroutine in our programs for oceanographic data management and manipulation.
We investigate a recently proposed Bayesian adaptation method for building style-adapted maximum entropy language models for speech recognition, given a large corpus of written language data and a small corpus of speech transcripts. Experiments show that the method consistently outperforms linear interpolation which is typically used in such cases.
LINEAR PREDICTION MODELS
Linear Prediction Coding Forward, Backward and Lattice Predictors Short-term and Long-Term Linear Predictors MAP Estimation of Predictor Coefficients Sub-Band Linear Prediction Signal Restoration Using Linear Prediction Models Summary
inear prediction modelling is used in a diverse area of applications, such as data forecasting, speech coding, video coding, speech recognition, model-based spectral analysis, model-based interpolation, signal restoration, and impulse/step event detection.
Calibration, Veriﬁcation, Statistical Treatment of Analytical Data, Detection Limits, and Quality Assurance/Quality Control
If you can measure that of which you speak, and can express it by a number, you know something of your subject, but if you cannot measure it, your knowledge is meager and unsatisfactory. —Lord Kelvin
CHAPTER AT A GLANCE
Good laboratory practice .........................................................................................38 Error in laboratory measurement ............................................................................