The adaptive Volterra filter (AVF) corresponding to nonlinear system is attractive due to its linear relationship between the input and output signals. However, the formidable computer complexity of AVF is prohibitive for its practical applications. This paper presents a design method of noise canceller by using a parallel fast recursive least squares (RLS) adaptive Volterra filter (PAVF). PAVF...

The Fisher information matrix of the cosmic microwave background (CMB) radiation power spectrum coefficients is a fundamental quantity that specifies the information content of a CMB experiment. In the most general case, its exact calculation scales with the third power of the number of data points N and is therefore computationally prohibitive for state-of-the-art surveys. Applicable to a very...

We present two benchmark suites for CORBA brokers, targeted at the broker vendor and user audiences respectively. The vendor suite is a result of several benchmarking projects with industrial partners, and covers the entire functionality of a CORBA broker. The user suite is simplified to give an overview of the basic factors influencing broker performance, and is complemented with an approach f...

We adopt the decision-theoretic principle of expected utility maximization as a paradigm for designing autonomous rational agents operating in multi-agent and mixed environments. Our approach is based on explicitly modeling other agents, human or artificial. The advantage of our approach is that explicit models are the most comprehensive tools one can use to guide meaningful interactions. The d...

We investigate the problem of determining a compact underspecified semantical representation for sentences that may be highly ambiguous. Due to combinatorial explosion, the naive method of building semantics for the different syntactic readings independently is prohibitive. We present a method that takes as input a syntactic parse forest with associated constraintbased semantic construction rul...

Recently, it has been shown that Bayesian Network Classifier (BNC), a generative model applied to a classification task, yields comparable performance to sophisticated discriminative methods such as SVMs and C4.5 [1]. Improved classification performance of BNCs is due, in part, to optimization of the conditional likelihood (CML) [2]. Unfortunately, the CML optimization, often implemented as a g...

Why similarity analytics? Similarity analytics are the best analysis tool for discovery of insights from big data. The value is in getting the data to tell you things you didn't know. This is a challenge best solved by looking for connections in the data. You just can't do this discovery with the standard analytics that come with a data warehouse. And doing this type of discovery over large dat...

on more and more computing facilities. However, this is an unsustainable solution as the industry practice continues to move toward more detailed modeling and financial reporting involving more stochastic components. In the foreseeable future, the costs of such nested simulations will be prohibitive even for the most resourceful companies. The running time of simulations can still be too long f...

(EPQ)1 is a self-report measure that operationalises Eysenck's model of personality.2 In addition to the original English language version,1there now exists a large number of foreign language translations,3,4 including Urdu.5,6 For both clinicians and researchers, the administration of 90 items may be prohibitive due to time or space constraints. Therefore a number of shorter measures,derived f...