The Experts below are selected from a list of 22869 Experts worldwide ranked by ideXlab platform

Ramasamy Krishnan - One of the best experts on this subject based on the ideXlab platform.

  • ICASSP - A single-channel ROM-based complex digital filter implementation in the quadratic residue number systems
    ICASSP-88. International Conference on Acoustics Speech and Signal Processing, 1
    Co-Authors: Ramasamy Krishnan
    Abstract:

    The implementation of complex digital filters using the quadratic residue number system (QRNs) and modified quadratic residue number system (MQRNS) is considered. These QRNS/MQRNS-based filter architectures are memory-intensive because the lookup-table approach has been used in the filter implementation. If the required number of lookup tables is reduced to a reasonable extent, single-chip VLSI implementation of such architectures may become practically feasible. A dual-clock Computational Module has been proposed to reduce the number of memory requirements in the QRNS/MQRNS-based complex digital filters. A direct FIR (finite-impulse response) filter architecture has been implemented using the proposed Computational Module in the QRNS and MQRNS schemes. >

Peter Van Der Meer - One of the best experts on this subject based on the ideXlab platform.

  • mean shift a robust approach toward feature space analysis
    IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002
    Co-Authors: Dorin Comaniciu, Peter Van Der Meer
    Abstract:

    A general non-parametric technique is proposed for the analysis of a complex multimodal feature space and to delineate arbitrarily shaped clusters in it. The basic Computational Module of the technique is an old pattern recognition procedure: the mean shift. For discrete data, we prove the convergence of a recursive mean shift procedure to the nearest stationary point of the underlying density function and, thus, its utility in detecting the modes of the density. The relation of the mean shift procedure to the Nadaraya-Watson estimator from kernel regression and the robust M-estimators; of location is also established. Algorithms for two low-level vision tasks discontinuity-preserving smoothing and image segmentation - are described as applications. In these algorithms, the only user-set parameter is the resolution of the analysis, and either gray-level or color images are accepted as input. Extensive experimental results illustrate their excellent performance.

  • Real-time tracking of non-rigid objects using mean shift
    Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2000
    Co-Authors: Dorin Comaniciu, Visvanathan Ramesh, Peter Van Der Meer
    Abstract:

    A new method for real time tracking of non-rigid objects seen from a moving camera is proposed. The central Computational Module is based on the mean shift iterations and finds the most probable target position in the current frame. The dissimilarity between the target model (its color distribution) and the target candidates is expressed by a metric derived from the Bhattacharyya coefficient. The theoretical analysis of the approach shows that it relates to the Bayesian framework while providing a practical, fast and efficient solution. The capability of the tracker to handle in real time partial occlusions, significant clutter, and target scale variations, is demonstrated for several image sequences

Themis Prodromakis - One of the best experts on this subject based on the ideXlab platform.

  • an analogue domain switch capacitor based arithmetic logic unit
    International Symposium on Circuits and Systems, 2019
    Co-Authors: Alexander Serb, Themis Prodromakis
    Abstract:

    The continuous maturation of novel nanoelectronic devices exhibiting finely tuneable resistive switching is rekindling interest in analogue-domain computation. Regardless of domain, a useful Computational Module is the arithmetic-logic unit (ALU), which is capable of performing one or more fundamental mathematical operations (typical example: addition and subtraction). In this work we report on a design for an analogue ALU (aALU) capable of performing barrel addition and subtraction (i.e. ADD/SUB in modular arithmetic). The circuit only requires 5 minimum-size transistors and 1 capacitor. We show that our aALU is in principle capable of handling 5 bits of information using a single input/output wire. Core power dissipation per operation is estimated to peak at ≈ 59 f J (input operand-dependent) in TSMC's 65 nm technology.

  • ISCAS - An Analogue-Domain, Switch-Capacitor-Based Arithmetic-Logic Unit
    2019 IEEE International Symposium on Circuits and Systems (ISCAS), 2019
    Co-Authors: Alexander Serb, Themis Prodromakis
    Abstract:

    The continuous maturation of novel nanoelectronic devices exhibiting finely tuneable resistive switching is rekindling interest in analogue-domain computation. Regardless of domain, a useful Computational Module is the arithmetic-logic unit (ALU), which is capable of performing one or more fundamental mathematical operations (typical example: addition and subtraction). In this work we report on a design for an analogue ALU (aALU) capable of performing barrel addition and subtraction (i.e. ADD/SUB in modular arithmetic). The circuit only requires 5 minimum-size transistors and 1 capacitor. We show that our aALU is in principle capable of handling 5 bits of information using a single input/output wire. Core power dissipation per operation is estimated to peak at ≈ 59 f J (input operand-dependent) in TSMC's 65 nm technology.

Dorin Comaniciu - One of the best experts on this subject based on the ideXlab platform.

  • mean shift a robust approach toward feature space analysis
    IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002
    Co-Authors: Dorin Comaniciu, Peter Van Der Meer
    Abstract:

    A general non-parametric technique is proposed for the analysis of a complex multimodal feature space and to delineate arbitrarily shaped clusters in it. The basic Computational Module of the technique is an old pattern recognition procedure: the mean shift. For discrete data, we prove the convergence of a recursive mean shift procedure to the nearest stationary point of the underlying density function and, thus, its utility in detecting the modes of the density. The relation of the mean shift procedure to the Nadaraya-Watson estimator from kernel regression and the robust M-estimators; of location is also established. Algorithms for two low-level vision tasks discontinuity-preserving smoothing and image segmentation - are described as applications. In these algorithms, the only user-set parameter is the resolution of the analysis, and either gray-level or color images are accepted as input. Extensive experimental results illustrate their excellent performance.

  • Real-time tracking of non-rigid objects using mean shift
    Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2000
    Co-Authors: Dorin Comaniciu, Visvanathan Ramesh, Peter Van Der Meer
    Abstract:

    A new method for real time tracking of non-rigid objects seen from a moving camera is proposed. The central Computational Module is based on the mean shift iterations and finds the most probable target position in the current frame. The dissimilarity between the target model (its color distribution) and the target candidates is expressed by a metric derived from the Bhattacharyya coefficient. The theoretical analysis of the approach shows that it relates to the Bayesian framework while providing a practical, fast and efficient solution. The capability of the tracker to handle in real time partial occlusions, significant clutter, and target scale variations, is demonstrated for several image sequences

Alexander Serb - One of the best experts on this subject based on the ideXlab platform.

  • an analogue domain switch capacitor based arithmetic logic unit
    International Symposium on Circuits and Systems, 2019
    Co-Authors: Alexander Serb, Themis Prodromakis
    Abstract:

    The continuous maturation of novel nanoelectronic devices exhibiting finely tuneable resistive switching is rekindling interest in analogue-domain computation. Regardless of domain, a useful Computational Module is the arithmetic-logic unit (ALU), which is capable of performing one or more fundamental mathematical operations (typical example: addition and subtraction). In this work we report on a design for an analogue ALU (aALU) capable of performing barrel addition and subtraction (i.e. ADD/SUB in modular arithmetic). The circuit only requires 5 minimum-size transistors and 1 capacitor. We show that our aALU is in principle capable of handling 5 bits of information using a single input/output wire. Core power dissipation per operation is estimated to peak at ≈ 59 f J (input operand-dependent) in TSMC's 65 nm technology.

  • ISCAS - An Analogue-Domain, Switch-Capacitor-Based Arithmetic-Logic Unit
    2019 IEEE International Symposium on Circuits and Systems (ISCAS), 2019
    Co-Authors: Alexander Serb, Themis Prodromakis
    Abstract:

    The continuous maturation of novel nanoelectronic devices exhibiting finely tuneable resistive switching is rekindling interest in analogue-domain computation. Regardless of domain, a useful Computational Module is the arithmetic-logic unit (ALU), which is capable of performing one or more fundamental mathematical operations (typical example: addition and subtraction). In this work we report on a design for an analogue ALU (aALU) capable of performing barrel addition and subtraction (i.e. ADD/SUB in modular arithmetic). The circuit only requires 5 minimum-size transistors and 1 capacitor. We show that our aALU is in principle capable of handling 5 bits of information using a single input/output wire. Core power dissipation per operation is estimated to peak at ≈ 59 f J (input operand-dependent) in TSMC's 65 nm technology.