2,830 research outputs found
Development of a dc-ac power conditioner for wind generator by using neural network
This project present of development single phase DC-AC converter for wind
generator application. The mathematical model of the wind generator and Artificial
Neural Network control for DC-AC converter is derived. The controller is designed to
stabilize the output voltage of DC-AC converter. To verify the effectiveness of the
proposal controller, both simulation and experimental are developed. The simulation and
experimental result show that the amplitude of output voltage of the DC-AC converter
can be controlled
Practical issues for the implementation of survivability and recovery techniques in optical networks
Entanglement Distribution in Optical Networks
The ability to generate entangled photon-pairs over a broad wavelength range
opens the door to the simultaneous distribution of entanglement to multiple
users in a network by using centralized sources and flexible
wavelength-division multiplexing schemes. Here we show the design of a
metropolitan optical network consisting of tree-type access networks whereby
entangled photon-pairs are distributed to any pair of users, independent of
their location. The network is constructed employing commercial off-the-shelf
components and uses the existing infrastructure, which allows for moderate
deployment costs. We further develop a channel plan and a network-architecture
design to provide a direct optical path between any pair of users, thus
allowing classical and one-way quantum communication as well as entanglement
distribution. This allows the simultaneous operation of multiple quantum
information technologies. Finally, we present a more flexible backbone
architecture that pushes away the load limitations of the original network
design by extending its reach, number of users and capabilities.Comment: 26 pages, 12 figure
Quantum Metropolitan Optical Network based on Wavelength Division Multiplexing
Quantum Key Distribution (QKD) is maturing quickly. However, the current
approaches to its application in optical networks make it an expensive
technology. QKD networks deployed to date are designed as a collection of
point-to-point, dedicated QKD links where non-neighboring nodes communicate
using the trusted repeater paradigm. We propose a novel optical network model
in which QKD systems share the communication infrastructure by wavelength
multiplexing their quantum and classical signals. The routing is done using
optical components within a metropolitan area which allows for a dynamically
any-to-any communication scheme. Moreover, it resembles a commercial telecom
network, takes advantage of existing infrastructure and utilizes commercial
components, allowing for an easy, cost-effective and reliable deployment.Comment: 23 pages, 8 figure
Principles of Neuromorphic Photonics
In an age overrun with information, the ability to process reams of data has
become crucial. The demand for data will continue to grow as smart gadgets
multiply and become increasingly integrated into our daily lives.
Next-generation industries in artificial intelligence services and
high-performance computing are so far supported by microelectronic platforms.
These data-intensive enterprises rely on continual improvements in hardware.
Their prospects are running up against a stark reality: conventional
one-size-fits-all solutions offered by digital electronics can no longer
satisfy this need, as Moore's law (exponential hardware scaling),
interconnection density, and the von Neumann architecture reach their limits.
With its superior speed and reconfigurability, analog photonics can provide
some relief to these problems; however, complex applications of analog
photonics have remained largely unexplored due to the absence of a robust
photonic integration industry. Recently, the landscape for
commercially-manufacturable photonic chips has been changing rapidly and now
promises to achieve economies of scale previously enjoyed solely by
microelectronics.
The scientific community has set out to build bridges between the domains of
photonic device physics and neural networks, giving rise to the field of
\emph{neuromorphic photonics}. This article reviews the recent progress in
integrated neuromorphic photonics. We provide an overview of neuromorphic
computing, discuss the associated technology (microelectronic and photonic)
platforms and compare their metric performance. We discuss photonic neural
network approaches and challenges for integrated neuromorphic photonic
processors while providing an in-depth description of photonic neurons and a
candidate interconnection architecture. We conclude with a future outlook of
neuro-inspired photonic processing.Comment: 28 pages, 19 figure
- …