The Experts below are selected from a list of 76422 Experts worldwide ranked by ideXlab platform
S A Jabar - One of the best experts on this subject based on the ideXlab platform.
-
Alternative architectures for bidirectional single-mode fiber SuperPON 512 ONU, 100 km
Network Architectures Management and Applications III, 2005Co-Authors: S A JabarAbstract:This paper presents alternative architectures for high split and long range bidirectional single mode fiber (SMF) super passive optical networks (SuperPONs). The erbium doped fiber amplifier (EDFA) is introduced to enhance power budget. Three different alternative architectures are studied: 1) using Transmission Speed of 10 Gbit/s and 2.5 Gbit/s at same wavelength of 1550 nm; 2) using same Transmission Speed of 10 Gbit/s at wavelength of 1550 nm for downstream and 1530 nm for upstream; 3) using bidirectional EDFA at Transmission Speed of 10 Gbit/s and 2.5 Gbit/s with same wavelength of 1550 nm. The elaboration of architectures together with their advantages and disadvantages are included. The feasibility of deploying a SuperPON with 512 optical network units (ONUs) at Transmission length of 100 km was observed from power budget studies.
-
minimization of amplified spontaneous emission noise in upstream superpon 512 onu 10 gbit s
Wireless and Optical Communications Networks, 2005Co-Authors: S A Jabar, Mohammad Yousif Jamro, John MAbstract:We demonstrated the effect of presenting optical band pass filter for point to multipoint architecture such SuperPON. The position of optical filter and the range of optical filter bandwidth to minimise amplified spontaneous emission noise for upstream SuperPON with 512 ONU at Transmission Speed of 10 Gbit/s is explored.
-
Minimization of amplified spontaneous emission noise in upstream SuperPON 512 ONU, 10 Gbit/s
Second IFIP International Conference on Wireless and Optical Communications Networks 2005. WOCN 2005., 1Co-Authors: S A Jabar, Mohammad Yousif Jamro, John M. SeniorAbstract:We demonstrated the effect of presenting optical band pass filter for point to multipoint architecture such SuperPON. The position of optical filter and the range of optical filter bandwidth to minimise amplified spontaneous emission noise for upstream SuperPON with 512 ONU at Transmission Speed of 10 Gbit/s is explored.
Franco Cacialli - One of the best experts on this subject based on the ideXlab platform.
-
Visible light communications: real time 10 Mb/s link with a low bandwidth polymer light-emitting diode.
Opt Express, 2014Co-Authors: Franco CacialliAbstract:This paper presents new experimental results on a polymer light-emitting diode based visible light communications system. For the first time we demonstrate a 10 Mb/s link based on the on-off keying data format with real time equalization on a field programmable gate array. The 10 Mb/s Transmission Speed is available at a bit error rate less than 4.6 × 10(-3), which is the limit for forward error correction. At a BER of 10(-6) a Transmission Speed of 7 Mb/s is readily achievable.
Axel Hutt - One of the best experts on this subject based on the ideXlab platform.
-
Neural field simulator: two-dimensional spatio-temporal dynamics involving finite Transmission Speed
Frontiers in Neuroinformatics, 2015Co-Authors: Eric Nichols, Axel HuttAbstract:Neural Field models (NFM) play an important role in the understanding of neural population dynamics on a mesoscopic spatial and temporal scale. Their numerical simulation is an essential element in the analysis of their spatio-temporal dynamics. The simulation tool described in this work considers scalar spatially homogeneous neural fields taking into account a finite axonal Transmission Speed and synaptic temporal derivatives of first and second order. A text-based interface offers complete control of field parameters and several approaches are used to accelerate simulations. A graphical output utilizes video hardware acceleration to display running output with reduced computational hindrance compared to simulators that are exclusively software-based. Diverse applications of the tool demonstrate breather oscillations, static and dynamic Turing patterns and activity spreading with finite propagation Speed. The simulator is open source to allow tailoring of code and this is presented with an extension use case.
-
Open-source numerical simulation tool for two-dimensional neural fields involving finite axonal Transmission Speed
2015Co-Authors: Eric Nichols, Kevin Green, Axel HuttAbstract:This work aims to provide an open source and cross-platform simulation tool that integrates numerically integral-differential equations in a two-dimensional quadratic spatial domain with periodic boundary conditions and finite axonal Transmission Speed inducing space-dependent delays.. The term I denotes the external stimulus, K is the synaptic connectivity kernel and S is the firing rate. Finite axonal Transmission Speed c induces space-dependent delays. Conventional implementations of two-dimensional integration with space-dependent delays are rather slow due to the missing convolution in the integral. It has been shown in a previous work that this unfortunate property can be overcome by introducing a spatio-temporal kernel, rendering the integral into a spatial integral and an integral over delays. Four major aspects accelerate the integration Speed: (a) the underlying numerical method is expedited with a fast Fourier transform in space (b) the simulator writes and executes its own code based on interface selections to efficiently calculate and display only the user-defined features (c) the displayed matrix is put onto the running system's graphics processing unit for hardware acceleration of the visualization (d) reduced rate of GPU uploads optimized for visual perception. The simulator gives the user full control of the variables by permitting free choice of all variables through a text-based interface. Two dimensional field matrices can be displayed in rich detail in a three-dimensional plot. The visualization of field data is easily modified by a keypress, performing functions such as moving, rotating, zooming and changing colors and axis limits. Images and videos can be saved and simulations can be paused and resumed using the keyboard. The software is open-source and written in Python.
-
Two-dimensional patterns in neural fields subject to finite Transmission Speed
BMC Neuroscience, 2014Co-Authors: Eric J Nichols, Axel Hutt, Kevin Green, Lennaert Van VeenAbstract:This work analyzes and implements finite axonal Transmission Speeds in two-dimensional neural populations. The biological significance of this is found in the rate of spatiotemporal change in voltage across neuronal tissue, which can be attributed to phenomena such as delays in spike propagation within axons, neurotransmitter activation and the time courses of neuron polarization and refraction. The authors build upon the finite Transmission Speed work in [1]. Linear analysis about a spatially homogeneous resting state of the neural population dynamics is performed. The analyses of the resulting analytical expressions guide the parameter selection for simulations. For simulation, computation of the Transmission-delayed convolution between the kernel and firing rates is performed with a fast Fourier transform as in [1]. The Neural Field Simulator [2] is used to simulate the activity of the field. We extended the simulator by the implementation of a large class of kernels reflecting global excitation, global inhibition, local excitation-lateral inhibition and local inhibition-lateral excitation. Moreover, we extended the tools by an automatic root finder to compute stationary states and an automatic root finder of the characteristic equation of the linear dynamics. These latter features facilitate the user to perform the linear analysis. Further adjustments to the simulator include a provision to modify neural field variables online while simulations are ongoing and three-dimensional displays of disparate parts of the neural field, such as the external input, kernel and firing rate. We find Turing patterns appear when starting the simulations with the derived conditions for stationary instability. This is shown in Figure 1(A,B,C). Simulations with travelling wave patterns are also performed using parameter sets for the non-stationary instabilities, and the effects of finite Transmission Speeds are analyzed and visualized. The software tool provides a large set of analysis and visualization tools, that promises to Speed up the analysis of two-dimensional neural field dynamics and hence accelerates research on neural population dynamics. Figure 1 A neural field simulation. A noisy field A evolving B into a Turing pattern C.
-
Two-dimensional patterns in neural fields subject to finite Transmission Speed
BMC Neuroscience, 2014Co-Authors: Eric Nichols, Axel Hutt, Kevin Green, Lennaert Van VeenAbstract:International audienceThis work analyzes and implements finite axonal Transmission Speeds in two-dimensional neural populations. The biological significance of this is found in the rate of spatiotemporal change in voltage across neuronal tissue, which can be attributed to phenomena such as delays in spike propagation within axons, neurotransmitter activation and the time courses of neuron polarization and refraction
Lennaert Van Veen - One of the best experts on this subject based on the ideXlab platform.
-
Two-dimensional patterns in neural fields subject to finite Transmission Speed
BMC Neuroscience, 2014Co-Authors: Eric J Nichols, Axel Hutt, Kevin Green, Lennaert Van VeenAbstract:This work analyzes and implements finite axonal Transmission Speeds in two-dimensional neural populations. The biological significance of this is found in the rate of spatiotemporal change in voltage across neuronal tissue, which can be attributed to phenomena such as delays in spike propagation within axons, neurotransmitter activation and the time courses of neuron polarization and refraction. The authors build upon the finite Transmission Speed work in [1]. Linear analysis about a spatially homogeneous resting state of the neural population dynamics is performed. The analyses of the resulting analytical expressions guide the parameter selection for simulations. For simulation, computation of the Transmission-delayed convolution between the kernel and firing rates is performed with a fast Fourier transform as in [1]. The Neural Field Simulator [2] is used to simulate the activity of the field. We extended the simulator by the implementation of a large class of kernels reflecting global excitation, global inhibition, local excitation-lateral inhibition and local inhibition-lateral excitation. Moreover, we extended the tools by an automatic root finder to compute stationary states and an automatic root finder of the characteristic equation of the linear dynamics. These latter features facilitate the user to perform the linear analysis. Further adjustments to the simulator include a provision to modify neural field variables online while simulations are ongoing and three-dimensional displays of disparate parts of the neural field, such as the external input, kernel and firing rate. We find Turing patterns appear when starting the simulations with the derived conditions for stationary instability. This is shown in Figure 1(A,B,C). Simulations with travelling wave patterns are also performed using parameter sets for the non-stationary instabilities, and the effects of finite Transmission Speeds are analyzed and visualized. The software tool provides a large set of analysis and visualization tools, that promises to Speed up the analysis of two-dimensional neural field dynamics and hence accelerates research on neural population dynamics. Figure 1 A neural field simulation. A noisy field A evolving B into a Turing pattern C.
-
Two-dimensional patterns in neural fields subject to finite Transmission Speed
BMC Neuroscience, 2014Co-Authors: Eric Nichols, Axel Hutt, Kevin Green, Lennaert Van VeenAbstract:International audienceThis work analyzes and implements finite axonal Transmission Speeds in two-dimensional neural populations. The biological significance of this is found in the rate of spatiotemporal change in voltage across neuronal tissue, which can be attributed to phenomena such as delays in spike propagation within axons, neurotransmitter activation and the time courses of neuron polarization and refraction
Eric Nichols - One of the best experts on this subject based on the ideXlab platform.
-
Neural field simulator: two-dimensional spatio-temporal dynamics involving finite Transmission Speed
Frontiers in Neuroinformatics, 2015Co-Authors: Eric Nichols, Axel HuttAbstract:Neural Field models (NFM) play an important role in the understanding of neural population dynamics on a mesoscopic spatial and temporal scale. Their numerical simulation is an essential element in the analysis of their spatio-temporal dynamics. The simulation tool described in this work considers scalar spatially homogeneous neural fields taking into account a finite axonal Transmission Speed and synaptic temporal derivatives of first and second order. A text-based interface offers complete control of field parameters and several approaches are used to accelerate simulations. A graphical output utilizes video hardware acceleration to display running output with reduced computational hindrance compared to simulators that are exclusively software-based. Diverse applications of the tool demonstrate breather oscillations, static and dynamic Turing patterns and activity spreading with finite propagation Speed. The simulator is open source to allow tailoring of code and this is presented with an extension use case.
-
Open-source numerical simulation tool for two-dimensional neural fields involving finite axonal Transmission Speed
2015Co-Authors: Eric Nichols, Kevin Green, Axel HuttAbstract:This work aims to provide an open source and cross-platform simulation tool that integrates numerically integral-differential equations in a two-dimensional quadratic spatial domain with periodic boundary conditions and finite axonal Transmission Speed inducing space-dependent delays.. The term I denotes the external stimulus, K is the synaptic connectivity kernel and S is the firing rate. Finite axonal Transmission Speed c induces space-dependent delays. Conventional implementations of two-dimensional integration with space-dependent delays are rather slow due to the missing convolution in the integral. It has been shown in a previous work that this unfortunate property can be overcome by introducing a spatio-temporal kernel, rendering the integral into a spatial integral and an integral over delays. Four major aspects accelerate the integration Speed: (a) the underlying numerical method is expedited with a fast Fourier transform in space (b) the simulator writes and executes its own code based on interface selections to efficiently calculate and display only the user-defined features (c) the displayed matrix is put onto the running system's graphics processing unit for hardware acceleration of the visualization (d) reduced rate of GPU uploads optimized for visual perception. The simulator gives the user full control of the variables by permitting free choice of all variables through a text-based interface. Two dimensional field matrices can be displayed in rich detail in a three-dimensional plot. The visualization of field data is easily modified by a keypress, performing functions such as moving, rotating, zooming and changing colors and axis limits. Images and videos can be saved and simulations can be paused and resumed using the keyboard. The software is open-source and written in Python.
-
Two-dimensional patterns in neural fields subject to finite Transmission Speed
BMC Neuroscience, 2014Co-Authors: Eric Nichols, Axel Hutt, Kevin Green, Lennaert Van VeenAbstract:International audienceThis work analyzes and implements finite axonal Transmission Speeds in two-dimensional neural populations. The biological significance of this is found in the rate of spatiotemporal change in voltage across neuronal tissue, which can be attributed to phenomena such as delays in spike propagation within axons, neurotransmitter activation and the time courses of neuron polarization and refraction
