21 research outputs found

    LINEARITY OF REGRESSION FOR NON-ADJACENT WEAK RECORDS

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    Abstract: A complete characterization of the family of distributions with linearity of regression for future non-adjacent weak records with spacing equal to two is given. Also, in the adjacent case, weak-record versions of some known characterization results for regular records are presented

    Gaussian conditional structure of the second order and the Kagan classification of multivariate distributions

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    The only Kagan-n,2(loc) probability measure with Gaussian conditional structure of the second order (GCS2) is a multivariate normal distribution. Also a short review of the known results on the GCS2 distributions is given.Kagan class Gaussian conditional structure of the second order multivariate normal law linearity of regression homoscedasticity characterization

    The origin of parental care in birds: a reassessment

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    energy expenditure; Ficedula hypoleuca; pied flycatcher; song

    Limit theorems for random permanents with exchangeable structure

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    Abstract Permanents of random matrices extend the concept of U-statistics with product kernels. In this paper, we study limiting behavior of permanents of random matrices with independent columns of exchangeable components. Our main results provide a general framework which unifies already existing asymptotic theory for projection matrices as well as matrices of all-iid entries. The method of the proofs is based on a Hoeffding-type orthogonal decomposition of a random permanent function. The decomposition allows us to relate asymptotic behavior of permanents to that of elementary symmetric polynomials based on triangular arrays of rowwise independent rv's. r 2004 Elsevier Inc. All rights reserved

    Linearity of regression for non-adjacent order statistics

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    Projection formulas for orthogonal polynomials. arxiv.org/abs/math.CA/0606092

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    Abstract We prove a new projection formula for the four-parameter family of orthogonal polynomials outside of the Askey-Wilson class. By carefully analyzing the recurrence relations we manage to overcome the lack of explicit expression for the orthogonality measure

    Power Backoff Reduction Techniques for Generalized Multicarrier Waveforms

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    Amplification of generalized multicarrier (GMC) signals by high-power amplifiers (HPAs) before transmission can result in undesirable out-of-band spectral components, necessitating power backoff, and low HPA efficiency. We evaluate variations of several peak-to-average power ratio (PAPR) reduction and HPA linearization techniques which were previously proposed for OFDM signals. Our main emphasis is on their applicability to the more general class of GMC signals, including serial modulation and DFT-precoded OFDM. Required power backoff is shown to depend on the type of signal transmitted, the specific HPA nonlinearity characteristic, and the spectrum mask which is imposed to limit adjacent channel interference. PAPR reduction and HPA linearization techniques are shown to be very effective when combined
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