Value decomposition

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  • An algorithm based on the Generalized Hebbian Algorithm is described that allows the singular value decomposition of a dataset to be learned based on single observation pairs presented serially. The algorithm has minimal memory requirements, and is therefore interesting in the natural language domain, where very large datasets are often used, and datasets quickly become intractable. The technique is demonstrated on the task of learning word and letter bigram pairs from text.

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  • Tuyển tập các báo cáo nghiên cứu khoa học trên tạp chí khoa học vật lý quốc tế đề tài: THE COVARIABILITY BETWEEN ANOMALOUS NORTHEAST MONSOON RAINFALL IN MALAYSIA AND SEA SURFACE TEMPERATURE IN INDIAN-PACIFIC SECTOR: A SINGULAR VALUE DECOMPOSITION ANALYSIS APPROACH

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  • Tuyển tập các báo cáo nghiên cứu về y học được đăng trên tạp chí y học Minireview cung cấp cho các bạn kiến thức về ngành y đề tài: Singular value decomposition-based regression identifies activation of endogenous signaling pathways in vivo...

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  • Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Applying Novel Time-Frequency Moments Singular Value Decomposition Method and Artificial Neural Networks for Ballistocardiography

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  • Most high resolution direction-of-arrival (DOA) estimation methods rely on subspace or eigenbased information which can be obtained fromthe eigenvalue decomposition (EVD) of an estimated correlation matrix, or from the singular value decomposition (SVD) of the corresponding data matrix.

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  • Most high resolution direction-of-arrival (DOA) estimation methods rely on subspace or eigenbased information which can be obtained fromthe eigenvalue decomposition (EVD) of an estimated correlation matrix, or from the singular value decomposition (SVD) of the corresponding data matrix. However, the expense of directly computing these decompositions is usually prohibitive for real-time processing. Also, because theDOAangles are typically time-varying, repeatedcomputation is necessarytotracktheangles.

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  • Ten years have elapsed since the second German edition of the present book was published. During this period the external appear- ance of the currency and banking problems of the world has com- pletely altered. But closer examination reveals that the same fundamental issues are being contested now as then. Then, England was on the way to raising the gold-value of the pound once more to its pre-war level.

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  • The debate is also reflected in the efforts to reform the regulatory environment in response to the current financial crisis. Brunnermeier et al. (2008) also conceptually distinguish between a regulatory and a market based notion of bank capital. When examining the roots of the crisis, Greenlaw et al. (2008) argue that banks’ active management of their capital structures in relation to internal value at risk, rather than regulatory constraints, was a key destabilising factor.

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  • In the framework of Black-Scholes-Merton option pricing models, by employing exotic options instead of plain options or warrants, this paper presents an equivalent decomposition method for the Callable Convertible Bonds (CCB). Furthermore, the analytic valuation formulae for CCB are obtained by using the analytic formulae for those simpler securities decomposed from CCB. This method is validated by comparing with Monte Carlo simulation. Besides, the effects of call clauses, coupon clauses, soft call condition clauses and dividend payment are analyzed respectively.

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  • There has been a time when statistical modeling of observation equations was clear in disciplines like geodesy, geophysics, photogrammetry and practically always based on the conceptual arsenal of least square theory despite the different physical realities and laws involved in their respective observations.

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  • The aim of this paper is to investigate the use of sample reweighting, in a behavioural tax microsimulation model, to examine the implications for government taxes and expenditure of population ageing in Australia. Tax microsimulation models are based on large-scale cross-sectional surveys containing substantial information about the characteristics of individuals and house- holds.

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  • These are the questions to be answered in this exploration of proj- ect management from the Zen perspective. Zen elicits an image of clear, quiet peacefulness, like a beautiful rock garden or a still pond set among pines with a full moon reflected in it. Projects and project management often elicit a very different im- age—drive, controlled chaos, tight schedules, restrictive budgets, anxi- ety, conflict, disappointment, accomplishment, value.

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  • We revisit the algorithm of Schütze (1995) for unsupervised part-of-speech tagging. The algorithm uses reduced-rank singular value decomposition followed by clustering to extract latent features from context distributions. As implemented here, it achieves state-of-the-art tagging accuracy at considerably less cost than more recent methods.

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  • The Singular Value Decomposition Trong phần 2, chúng ta đã thấy rằng một ma trận biến đổi vectơ trong phạm vi của nó vào vectơ trong phạm vi của nó (cột không gian), và vector trong không gian vô giá trị của nó vào vector không. Không có vector khác không được ánh xạ vào không gian vô giá trị trái, đó là, vào bổ sung trực giao của phạm vi. Trong phần này, chúng tôi thực hiện tuyên bố này cụ thể hơn bằng cách hiển thị vectors1 đơn vị trong rowspace được biến đổi bởi ma trận....

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  • The annual IRS cross-sections are stratified samples, with the probability of inclusion rising steeply with total income. 6 Variables includemost of the values from the 1040 tax form and associated schedules, as well as data from Social Security records, such as the age and gender of each individual represented on the return. 7 The 1987 cross-sectional sample of about 88,000 returns is the base year of the panel. The panel was constructed by matching, in each subsequent year, the full population of tax returns that appeared in the 1987 sample.

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  • C H A P T E R 9 Long distance – analysing time series data Chapter objectives This chapter will help you to: ■ ■ ■ ■ ■ ■ identify the components of time series employ classical decomposition to analyse time series data produce forecasts of future values of time series variables apply exponential smoothing to analyse time series data use the technology:

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  • In composting stable manure in the most economical manner, the evaporation of the organic parts and the leaching of the ashy (and other) portions must be avoided, while the condition of the mass is such as to admit of the perfect decomposition of the manure. Solid manures in their fresh state are of but very little use to plants. It is only as they are decomposed, and have their nitrogen turned into ammonia, and their other ingredients resolved into the condition required by plants, that they are of much value as fertilizers. We have seen that, if this decomposition...

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  • In composting stable manure in the most economical manner, the evaporation of the organic parts and the leaching of the ashy (and other) portions must be avoided, while the condition of the mass is such as to admit of the perfect decomposition of the manure. Solid manures in their fresh state are of but very little use to plants. It is only as they are decomposed, and have their nitrogen turned into ammonia, and their other ingredients resolved into the condition required by plants, that they are of much value as fertilizers. We have seen that, if this decomposition takes...

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  • Our results indicate that the assumed structural identi cation scheme is compatible with the data. Based on the con rmed identi cation of funda- mental and nonfundamental shocks, the historical stock prices are decom- posed into fundamental components and nonfundamental components. In contrast to Binswanger (2004), the decomposition shows that the linkage be- tween Japanese stock prices and real activity shocks became strengthened since the bubble collapsed in the beginning of 1990s.

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