3,764 research outputs found
Study of spread spectrum multiple access systems for satellite communications with overlay on current services
The feasibility of using spread spectrum techniques to provide a low-cost multiple access system for a very large number of low data terminals was investigated. Two applications of spread spectrum technology to very small aperture terminal (VSAT) satellite communication networks are presented. Two spread spectrum multiple access systems which use a form of noncoherent M-ary FSK (MFSK) as the primary modulation are described and the throughput analyzed. The analysis considers such factors as satellite power constraints and adjacent satellite interference. Also considered is the effect of on-board processing on the multiple access efficiency and the feasibility of overlaying low data rate spread spectrum signals on existing satellite traffic as a form of frequency reuse is investigated. The use of chirp is examined for spread spectrum communications. In a chirp communication system, each data bit is converted into one or more up or down sweeps of frequency, which spread the RF energy across a broad range of frequencies. Several different forms of chirp communication systems are considered, and a multiple-chirp coded system is proposed for overlay service. The mutual interference problem is examined in detail and a performance analysis undertaken for the case of a chirp data channel overlaid on a video channel
An Expressive Language and Efficient Execution System for Software Agents
Software agents can be used to automate many of the tedious, time-consuming
information processing tasks that humans currently have to complete manually.
However, to do so, agent plans must be capable of representing the myriad of
actions and control flows required to perform those tasks. In addition, since
these tasks can require integrating multiple sources of remote information ?
typically, a slow, I/O-bound process ? it is desirable to make execution as
efficient as possible. To address both of these needs, we present a flexible
software agent plan language and a highly parallel execution system that enable
the efficient execution of expressive agent plans. The plan language allows
complex tasks to be more easily expressed by providing a variety of operators
for flexibly processing the data as well as supporting subplans (for
modularity) and recursion (for indeterminate looping). The executor is based on
a streaming dataflow model of execution to maximize the amount of operator and
data parallelism possible at runtime. We have implemented both the language and
executor in a system called THESEUS. Our results from testing THESEUS show that
streaming dataflow execution can yield significant speedups over both
traditional serial (von Neumann) as well as non-streaming dataflow-style
execution that existing software and robot agent execution systems currently
support. In addition, we show how plans written in the language we present can
represent certain types of subtasks that cannot be accomplished using the
languages supported by network query engines. Finally, we demonstrate that the
increased expressivity of our plan language does not hamper performance;
specifically, we show how data can be integrated from multiple remote sources
just as efficiently using our architecture as is possible with a
state-of-the-art streaming-dataflow network query engine
Exploration and Design of High Performance Variation Tolerant On-Chip Interconnects
Siirretty Doriast
Event-based Vision: A Survey
Event cameras are bio-inspired sensors that differ from conventional frame
cameras: Instead of capturing images at a fixed rate, they asynchronously
measure per-pixel brightness changes, and output a stream of events that encode
the time, location and sign of the brightness changes. Event cameras offer
attractive properties compared to traditional cameras: high temporal resolution
(in the order of microseconds), very high dynamic range (140 dB vs. 60 dB), low
power consumption, and high pixel bandwidth (on the order of kHz) resulting in
reduced motion blur. Hence, event cameras have a large potential for robotics
and computer vision in challenging scenarios for traditional cameras, such as
low-latency, high speed, and high dynamic range. However, novel methods are
required to process the unconventional output of these sensors in order to
unlock their potential. This paper provides a comprehensive overview of the
emerging field of event-based vision, with a focus on the applications and the
algorithms developed to unlock the outstanding properties of event cameras. We
present event cameras from their working principle, the actual sensors that are
available and the tasks that they have been used for, from low-level vision
(feature detection and tracking, optic flow, etc.) to high-level vision
(reconstruction, segmentation, recognition). We also discuss the techniques
developed to process events, including learning-based techniques, as well as
specialized processors for these novel sensors, such as spiking neural
networks. Additionally, we highlight the challenges that remain to be tackled
and the opportunities that lie ahead in the search for a more efficient,
bio-inspired way for machines to perceive and interact with the world
Space shuttle avionics system
The Space Shuttle avionics system, which was conceived in the early 1970's and became operational in the 1980's represents a significant advancement of avionics system technology in the areas of systems and redundacy management, digital data base technology, flight software, flight control integration, digital fly-by-wire technology, crew display interface, and operational concepts. The origins and the evolution of the system are traced; the requirements, the constraints, and other factors which led to the final configuration are outlined; and the functional operation of the system is described. An overall system block diagram is included
Noisy Rumor Spreading and Plurality Consensus
Error-correcting codes are efficient methods for handling \emph{noisy}
communication channels in the context of technological networks. However, such
elaborate methods differ a lot from the unsophisticated way biological entities
are supposed to communicate. Yet, it has been recently shown by Feinerman,
Haeupler, and Korman {[}PODC 2014{]} that complex coordination tasks such as
\emph{rumor spreading} and \emph{majority consensus} can plausibly be achieved
in biological systems subject to noisy communication channels, where every
message transferred through a channel remains intact with small probability
, without using coding techniques. This result is a
considerable step towards a better understanding of the way biological entities
may cooperate. It has been nevertheless be established only in the case of
2-valued \emph{opinions}: rumor spreading aims at broadcasting a single-bit
opinion to all nodes, and majority consensus aims at leading all nodes to adopt
the single-bit opinion that was initially present in the system with (relative)
majority. In this paper, we extend this previous work to -valued opinions,
for any .
Our extension requires to address a series of important issues, some
conceptual, others technical. We had to entirely revisit the notion of noise,
for handling channels carrying -\emph{valued} messages. In fact, we
precisely characterize the type of noise patterns for which plurality consensus
is solvable. Also, a key result employed in the bivalued case by Feinerman et
al. is an estimate of the probability of observing the most frequent opinion
from observing the mode of a small sample. We generalize this result to the
multivalued case by providing a new analytical proof for the bivalued case that
is amenable to be extended, by induction, and that is of independent interest.Comment: Minor revisio
Neuromorphic Implementation of Orientation Hypercolumns
Neurons in the mammalian primary visual cortex are selective along multiple stimulus dimensions, including retinal position, spatial frequency, and orientation. Neurons tuned to different stimulus features but the same retinal position are grouped into retinotopic arrays of hypercolumns. This paper describes a neuromorphic implementation of orientation hypercolumns, which consists of a single silicon retina feeding multiple chips, each of which contains an array of neurons tuned to the same orientation and spatial frequency, but different retinal locations. All chips operate in continuous time, and communicate with each other using spikes transmitted by the address-event representation protocol. This system is modular in the sense that orientation coverage can be increased simply by adding more chips, and expandable in the sense that its output can be used to construct neurons tuned to other stimulus dimensions. We present measured results from the system, demonstrating neuronal selectivity along position, spatial frequency and orientation. We also demonstrate that the system supports recurrent feedback between neurons within one hypercolumn, even though they reside on different chips. The measured results from the system are in excellent concordance with theoretical predictions
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Space-time-frequency methods for interference-limited communication systems
textTraditionally, noise in communication systems has been modeled as an additive, white Gaussian noise process with independent, identically distributed samples. Although this model accurately reflects thermal noise present in communication system electronics, it fails to capture the statistics of interference and other sources of noise, e.g. in unlicensed communication bands. Modern communication system designers must take into account interference and non-Gaussian noise to maximize efficiencies and capacities of current and future communication networks. In this work, I develop new multi-dimensional signal processing methods to improve performance of communication systems in three applications areas: (i) underwater acoustic, (ii) powerline, and (iii) multi-antenna cellular. In underwater acoustic communications, I address impairments caused by strong, time-varying and Doppler-spread reverberations (self-interference) using adaptive space-time signal processing methods. I apply these methods to array receivers with a large number of elements. In powerline communications, I address impairments caused by non-Gaussian noise arising from devices sharing the powerline. I develop and apply a cyclic adaptive modulation and coding scheme and a factor-graph-based impulsive noise mitigation method to improve signal quality and boost link throughput and robustness. In cellular communications, I develop a low-latency, high-throughput space-time-frequency processing framework used for large scale (up to 128 antenna) MIMO. This framework is used in the world's first 100-antenna MIMO system and processes up to 492 Gbps raw baseband samples in the uplink and downlink directions. My methods prove that multi-dimensional processing methods can be applied to increase communication system performance without sacrificing real-time requirements.Electrical and Computer Engineerin
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