4,554 research outputs found
Evolution of associative learning in chemical networks
Organisms that can learn about their environment and modify their behaviour appropriately during their lifetime are more likely to survive and reproduce than organisms that do not. While associative learning – the ability to detect correlated features of the environment – has been studied extensively in nervous systems, where the underlying mechanisms are reasonably well understood, mechanisms within single cells that could allow associative learning have received little attention. Here, using in silico evolution of chemical networks, we show that there exists a diversity of remarkably simple and plausible chemical solutions to the associative learning problem, the simplest of which uses only one core chemical reaction. We then asked to what extent a linear combination of chemical concentrations in the network could approximate the ideal Bayesian posterior of an environment given the stimulus history so far? This Bayesian analysis revealed the ’memory traces’ of the chemical network. The implication of this paper is that there is little reason to believe that a lack of suitable phenotypic variation would prevent associative learning from evolving in cell signalling, metabolic, gene regulatory, or a mixture of these networks in cells
Timing subsystem development: Network synchronization experiments
This paper describes a program in which several experimental timing subsystem prototypes were designed, fabricated, and field tested using a small network of troposcatter and microwave digital communication links. This equipment was responsible for modem/radio interfacing, time interval measurement, clock adjustment and distribution, synchronization technique, and node to node information exchange. Presented are discussions of the design approach, measurement plan, and performance assessment methods. Recommendations are made based on the findings of the test program and an evaluation of the design of both the hardware and software elements of the timing subsystem prototypes
Asynchronous techniques for system-on-chip design
SoC design will require asynchronous techniques as the large parameter variations across the chip will make it impossible to control delays in clock networks and other global signals efficiently. Initially, SoCs will be globally asynchronous and locally synchronous (GALS). But the complexity of the numerous asynchronous/synchronous interfaces required in a GALS will eventually lead to entirely asynchronous solutions. This paper introduces the main design principles, methods, and building blocks for asynchronous VLSI systems, with an emphasis on communication and synchronization. Asynchronous circuits with the only delay assumption of isochronic forks are called quasi-delay-insensitive (QDI). QDI is used in the paper as the basis for asynchronous logic. The paper discusses asynchronous handshake protocols for communication and the notion of validity/neutrality tests, and completion tree. Basic building blocks for sequencing, storage, function evaluation, and buses are described, and two alternative methods for the implementation of an arbitrary computation are explained. Issues of arbitration, and synchronization play an important role in complex distributed systems and especially in GALS. The two main asynchronous/synchronous interfaces needed in GALS-one based on synchronizer, the other on stoppable clock-are described and analyzed
Efficient Neural Network Implementations on Parallel Embedded Platforms Applied to Real-Time Torque-Vectoring Optimization Using Predictions for Multi-Motor Electric Vehicles
The combination of machine learning and heterogeneous embedded platforms enables new potential for developing sophisticated control concepts which are applicable to the field of vehicle dynamics and ADAS. This interdisciplinary work provides enabler solutions -ultimately implementing fast predictions using neural networks (NNs) on field programmable gate arrays (FPGAs) and graphical processing units (GPUs)- while applying them to a challenging application: Torque Vectoring on a multi-electric-motor vehicle for enhanced vehicle dynamics. The foundation motivating this work is provided by discussing multiple domains of the technological context as well as the constraints related to the automotive field, which contrast with the attractiveness of exploiting the capabilities of new embedded platforms to apply advanced control algorithms for complex control problems. In this particular case we target enhanced vehicle dynamics on a multi-motor electric vehicle benefiting from the greater degrees of freedom and controllability offered by such powertrains. Considering the constraints of the application and the implications of the selected multivariable optimization challenge, we propose a NN to provide batch predictions for real-time optimization. This leads to the major contribution of this work: efficient NN implementations on two intrinsically parallel embedded platforms, a GPU and a FPGA, following an analysis of theoretical and practical implications of their different operating paradigms, in order to efficiently harness their computing potential while gaining insight into their peculiarities. The achieved results exceed the expectations and additionally provide a representative illustration of the strengths and weaknesses of each kind of platform. Consequently, having shown the applicability of the proposed solutions, this work contributes valuable enablers also for further developments following similar fundamental principles.Some of the results presented in this work are related to activities within the 3Ccar project, which has
received funding from ECSEL Joint Undertaking under grant agreement No. 662192. This Joint Undertaking
received support from the European Union’s Horizon 2020 research and innovation programme and Germany,
Austria, Czech Republic, Romania, Belgium, United Kingdom, France, Netherlands, Latvia, Finland, Spain, Italy,
Lithuania. This work was also partly supported by the project ENABLES3, which received funding from ECSEL
Joint Undertaking under grant agreement No. 692455-2
The QUEST large area CCD camera
We have designed, constructed, and put into operation a very large area CCD camera that covers the field of view of the 1.2 m Samuel Oschin Schmidt Telescope at the Palomar Observatory. The camera consists of 112 CCDs arranged in a mosaic of four rows with 28 CCDs each. The CCDs are 600 x 2400 pixel Sarnoff thinned, back-illuminated devices with 13 µm x 13 µm pixels. The camera covers an area of 4.6° x 3.6° on the sky with an active area of 9.6 deg_2. This camera has been installed at the prime focus of the telescope and commissioned, and scientific-quality observations on the Palomar-QUEST Variability Sky Survey were started in 2003 September. The design considerations, construction features, and performance parameters of this camera are described in this paper
Implementation of ILLIAC 4 algorithms for multispectral image interpretation
Research has focused on the design and partial implementation of a comprehensive ILLIAC software system for computer-assisted interpretation of multispectral earth resources data such as that now collected by the Earth Resources Technology Satellite. Research suggests generally that the ILLIAC 4 should be as much as two orders of magnitude more cost effective than serial processing computers for digital interpretation of ERTS imagery via multivariate statistical classification techniques. The potential of the ARPA Network as a mechanism for interfacing geographically-dispersed users to an ILLIAC 4 image processing facility is discussed
THE APPLICATION OF REAL-TIME SOFTWARE IN THE IMPLEMENTATION OF LOW-COST SATELLITE RETURN LINKS
Digital Signal Processors (DSPs) have evolved to a level where it is feasible
for digital modems with relatively low data rates to be implemented entirely with
software algorithms. With current technology it is still necessary for analogue
processing between the RF input and a low frequency IF but, as DSP technology
advances, it will become possible to shift the interface between analogue and digital
domains ever closer towards the RF input. The software radio concept is a long-term
goal which aims to realise software-based digital modems which are completely
flexible in terms of operating frequency, bandwidth, modulation format and source
coding. The ideal software radio cannot be realised until DSP, Analogue to Digital
(A/D) and Digital to Analogue (D/A) technology has advanced sufficiently. Until
these advances have been made, it is often necessary to sacrifice optimum
performance in order to achieve real-time operation. This Thesis investigates practical
real-time algorithms for carrier frequency synchronisation, symbol timing
synchronisation, modulation, demodulation and FEC. Included in this work are novel
software-based transceivers for continuous-mode transmission, burst-mode
transmission, frequency modulation, phase modulation and orthogonal frequency
division multiplexing (OFDM).
Ideal applications for this work combine the requirement for flexible baseband
signal processing and a relatively low data rate. Suitable applications for this work
were identified in low-cost satellite return links, and specifically in asymmetric
satellite Internet delivery systems. These systems employ a high-speed (>>2Mbps)
DVB channel from service provider to customer and a low-cost, low-speed (32-128
kbps) return channel. This Thesis also discusses asymmetric satellite Internet delivery
systems, practical considerations for their implementation and the techniques that are
required to map TCP/IP traffic to low-cost satellite return links
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