The Experts below are selected from a list of 11514 Experts worldwide ranked by ideXlab platform

Irina Gheorghiciuc - One of the best experts on this subject based on the ideXlab platform.

  • the subWord complexity of a class of infinite Binary Words
    Advances in Applied Mathematics, 2007
    Co-Authors: Irina Gheorghiciuc
    Abstract:

    The gap function of an infinite Word over the Binary alphabet {0,1} gives the distances between consecutive 1's in this Word. In this paper we study infinite Binary Words whose gap function is injective or ''almost injective.'' A method for computing the subWord complexity of such Words is given. A necessary and sufficient condition for a function to be the subWord complexity function of a Binary Word whose gap function is increasing is obtained.

  • The subWord complexity of a class of infinite Binary Words
    arXiv: Combinatorics, 2005
    Co-Authors: Irina Gheorghiciuc
    Abstract:

    Let $A_q$ be a $q$-letter alphabet and $w$ be a right infinite Word on this alphabet. A subWord of $w$ is a block of consecutive letters of $w$. The subWord complexity function of $w$ assigns to each positive integer $n$ the number $f_w(n)$ of distinct subWords of length $n$ of $w$. The gap function of an infinite Word over the Binary alphabet $\{0,1 \}$ gives the distances between consecutive 1's in this Word. In this paper we study infinite Binary Words whose gap function is injective or "almost injective". A method for computing the subWord complexity of such Words is given. A necessary and sufficient condition for a function to be the subWord complexity function of a Binary Word whose gap function is strictly increasing is obtained.

Karlmichael Schneider - One of the best experts on this subject based on the ideXlab platform.

  • on Word frequency information and negative evidence in naive bayes text classification
    International conference natural language processing, 2004
    Co-Authors: Karlmichael Schneider
    Abstract:

    The Naive Bayes classifier exists in different versions. One version, called multi-variate Bernoulli or Binary independence model, uses Binary Word occurrence vectors, while the multinomial model uses Word frequency counts. Many publications cite this difference as the main reason for the superior performance of the multinomial Naive Bayesclassifier. We argue that this is not true. We show that when all Word frequency information is eliminated from the document vectors, the multinomial Naive Bayes model performs even better. Moreover, we argue that the main reason for the difference in performance is the way that negative evidence, i.e. evidence from Words that do not occur in a document, is incorporated in the model. Therefore, this paper aims at a better understanding and a clarification of the difference between the two probabilistic models of Naive Bayes.

Bryan Usevitch - One of the best experts on this subject based on the ideXlab platform.

  • Fixed-point error analysis of two-channel perfect reconstruction filter banks with perfect alias cancellation
    42nd Midwest Symposium on Circuits and Systems (Cat. No.99CH36356), 1999
    Co-Authors: Bryan Usevitch, C. Betancourt
    Abstract:

    This paper studies the effects of fixed-point arithmetic in two-channel perfect reconstruction filter banks. Practical implementations of filter banks often require scaling of coefficients and differing Binary Word sizes to maintain dynamic range. When scaling is used with fixed precision arithmetic, the perfect alias cancellation (PAC) and perfect reconstruction (PR) constraints no longer hold. The main contribution of this paper is the derivation of constraints whereby PAC is maintained, even when coefficients are scaled and when the analysis and synthesis filter banks use different Binary Word lengths. Once PAC is established, the fixed-point effects on PR properties can be analyzed using standard methods. The theory is verified by comparing predicted and actual reconstruction signal-to-noise ratios (SNR's) resulting from simulating a symmetric wavelet transform (SWT).

  • Fixed-point error analysis of two-channel perfect reconstruction filter banks with perfect alias cancellation
    IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing, 1999
    Co-Authors: Bryan Usevitch, C.l. Betancourt
    Abstract:

    This paper studies the effects of fixed-point arithmetic in two-channel perfect reconstruction (PR) filter banks. Practical implementations of filter banks often require scaling of coefficients and differing Binary Word sizes to maintain dynamic range. When scaling is used with fixed precision arithmetic, the perfect alias cancellation (PAC) and PR constraints no longer hold. The main contribution of this paper is the derivation of constraints whereby PAC is maintained, even when coefficients are scaled and when the analysis and synthesis filter banks use different Binary Word lengths. Once PAC is established, the fixed-point effects on PR properties can be analyzed using standard methods. The theory is verified by comparing predicted and actual reconstruction signal-to-noise ratios resulting from simulating a symmetric wavelet transform.

James R. Mcdonald - One of the best experts on this subject based on the ideXlab platform.

  • error analysis of an optical current transducer operating with a digital signal processing system
    IEEE Transactions on Instrumentation and Measurement, 2000
    Co-Authors: Pawel Niewczas, Andrew Cruden, W.c. Michie, W.i. Madden, James R. Mcdonald
    Abstract:

    This paper analyzes errors associated with the analog-to-digital (A/D) conversion process of a digital signal processing unit (DSP) within the operation of an optical current transducer (OCT). Quantization of the analog current measurement signal leads to measurement errors which are a direct consequence of the uncertainty with which an N-bit resolution A/D assigns a Binary Word for a given analog input value. This paper presents comprehensive simulations of the performance of different current sensors monitored by the DSP unit and discusses aspects of compatibility between the sensor dynamic range and the resolution of an A/D conversion process. Recommendations are given on how to match the OCT to the given A/D parameters, and vice versa, in order to meet specified accuracy requirements.

  • Error analysis of an optical current transducer operating with a digital signal processing system
    IMTC 99. Proceedings of the 16th IEEE Instrumentation and Measurement Technology Conference (Cat. No.99CH36309), 2026
    Co-Authors: Pawel Niewczas, Andrew Cruden, W.c. Michie, W.i. Madden, James R. Mcdonald
    Abstract:

    This paper analyses errors associated with the analogue-to-digital conversion process of a digital signal processing unit (DSP) within the operation of an Optical Current Transducer (OCT). Quantisation of the analogue current measurement signal leads to measurement errors which are a direct consequence of the uncertainty with which an N-bit resolution analogue-to-digital converter assigns a Binary Word for a given analogue input value. This paper presents comprehensive simulations of the performance of different current sensors monitored by the DSP unit and discusses aspects of compatibility between the sensor dynamic range and the resolution of an analogue-to-digital conversion process. Recommendations are given on how to match the OCT to the given A/D parameters, and vice versa, in order to meet specified accuracy requirements.

C. Betancourt - One of the best experts on this subject based on the ideXlab platform.

  • Fixed-point error analysis of two-channel perfect reconstruction filter banks with perfect alias cancellation
    42nd Midwest Symposium on Circuits and Systems (Cat. No.99CH36356), 1999
    Co-Authors: Bryan Usevitch, C. Betancourt
    Abstract:

    This paper studies the effects of fixed-point arithmetic in two-channel perfect reconstruction filter banks. Practical implementations of filter banks often require scaling of coefficients and differing Binary Word sizes to maintain dynamic range. When scaling is used with fixed precision arithmetic, the perfect alias cancellation (PAC) and perfect reconstruction (PR) constraints no longer hold. The main contribution of this paper is the derivation of constraints whereby PAC is maintained, even when coefficients are scaled and when the analysis and synthesis filter banks use different Binary Word lengths. Once PAC is established, the fixed-point effects on PR properties can be analyzed using standard methods. The theory is verified by comparing predicted and actual reconstruction signal-to-noise ratios (SNR's) resulting from simulating a symmetric wavelet transform (SWT).