Search results for "hardware"

Support Tool for the Combined Software/Hardware Design of On-Chip ELM Training for SLFF Neural Networks

2016

Typically, hardware implemented neural networks are trained before implementation. Extreme learning machine (ELM) is a noniterative training method for single-layer feed-forward (SLFF) neural networks well suited for hardware implementation. It provides fixed-time learning and simplifies retraining of a neural network once implemented, which is very important in applications demanding on-chip training. This study proposes the data flow of a software support tool in the design process of a hardware implementation of on-chip ELM learning for SLFF neural networks. The software tool allows the user to obtain the optimal definition of functional and hardware parameters for any application, and e…

A 4K-Input High-Speed Winner-Take-All (WTA) Circuit with Single-Winner Selection for Change-Driven Vision Sensors

2019

Winner-Take-All (WTA) circuits play an important role in applications where a single element must be selected according to its relevance. They have been successfully applied in neural networks and vision sensors. These applications usually require a large number of inputs for the WTA circuit, especially for vision applications where thousands to millions of pixels may compete to be selected. WTA circuits usually exhibit poor response-time scaling with the number of competitors, and most of the current WTA implementations are designed to work with less than 100 inputs. Another problem related to the large number of inputs is the difficulty to select just one winner, since many competitors ma…

Efficient MLP Digital Implementation on FPGA

2005

The efficiency and the accuracy of a digital feed-forward neural networks must be optimized to obtain both high classification rate and minimum area on chip. In this paper an efficient MLP digital implementation. The key features of the hardware implementation are the virtual neuron based architecture and the use of the sinusoidal activation function for the hidden layer. The effectiveness of the proposed solutions has been evaluated developing different FPGA based neural prototypes for the High Energy Physics domain and the automatic Road Sign Recognition domain. The use of the sinusoidal activation function decreases hardware resource employment of about 32% when compared with the standar…

Two-level branch prediction using neural networks

2003

Dynamic branch prediction in high-performance processors is a specific instance of a general time series prediction problem that occurs in many areas of science. Most branch prediction research focuses on two-level adaptive branch prediction techniques, a very specific solution to the branch prediction problem. An alternative approach is to look to other application areas and fields for novel solutions to the problem. In this paper, we examine the application of neural networks to dynamic branch prediction. We retain the first level history register of conventional two-level predictors and replace the second level PHT with a neural network. Two neural networks are considered: a learning vec…

The FRAM robotic telescope for atmospheric monitoring at the Pierre Auger Observatory

2021

FRAM (F/Photometric Robotic Atmospheric Monitor) is a robotic telescope operated at the Pierre Auger Observatory in Argentina for the purposes of atmospheric monitoring using stellar photometry. As a passive system which does not produce any light that could interfere with the observations of the fluorescence telescopes of the observatory, it complements the active monitoring systems that use lasers. We discuss the applications of stellar photometry for atmospheric monitoring at optical observatories in general and the particular modes of operation employed by the Auger FRAM. We describe in detail the technical aspects of FRAM, the hardware and software requirements for a successful operati…

Genre-dependent effects of 3D film on presence, motion sickness, and protagonist perception

2016

Do the increasingly popular 3D movies change how we perceive the content of the movie? We presented short (3.21 min) film sequences to observers equipped with shutter glasses. Three genres (horror, action, and documentary) were crossed with three between-subjects viewing conditions (director’s 3D, artificial 3D, and 2D). Observers had to rate how the film impressed them in terms of arousal, motion sickness, presence, and immersion. They also judged the personality, attractiveness, and intelligence of the protagonist in all viewing conditions. Not surprisingly, horror films produced more arousal and presence than action films. Documentaries scored lowest on presence. Action movies produced t…

Predicting mid-air gestural interaction with public displays based on audience behaviour

2020

Abstract Knowledge about the expected interaction duration and expected distance from which users will interact with public displays can be useful in many ways. For example, knowing upfront that a certain setup will lead to shorter interactions can nudge space owners to alter the setup. If a system can predict that incoming users will interact at a long distance for a short amount of time, it can accordingly show shorter versions of content (e.g., videos/advertisements) and employ at-a-distance interaction modalities (e.g., mid-air gestures). In this work, we propose a method to build models for predicting users’ interaction duration and distance in public display environments, focusing on …

2015

Visuo-auditory sensory substitution systems are augmented reality devices that translate a video stream into an audio stream in order to help the blind in daily tasks requiring visuo-spatial information. In this work, we present both a new mobile device and a transcoding method specifically designed to sonify moving objects. Frame differencing is used to extract spatial features from the video stream and two-dimensional spatial information is converted into audio cues using pitch, interaural time difference and interaural level difference. Using numerical methods, we attempt to reconstruct visuo-spatial information based on audio signals generated from various video stimuli. We show that de…

Efficient techniques for energy saving in data center networks

2018

Data centers are constructed with a huge number of network devices to support the expanding cloud based services. These devices are used to achieve the highest performance in case of full utilization of the network. However, the peak capacity of the network is rarely reached. Consequently, many devices are set into idle state and cause a huge energy waste leading to a non-proportionality between the network load and the energy consumed. In this paper, we propose a new approach to improve the efficiency of data centers in terms of energy consumption. Our approach exploits the correlation in time of the inter-node communication traffic and some topological features to maximize energy saving w…

High temperature solid-catalized transesterification for biodiesel production

2010

Biodiesel has become more attractive recently because of its environmental benefits and the fact that it is made from renewable resources. Biodiesel is a mixture of monoalkyl esters of long chain fatty acids derived from renewable feed stock like vegetable oils and animal fats, mainly made of fatty acid glycerides. It is produced by transesterification processes in which oil or fat are reacted with a monohydric alcohol in the presence of a catalyst. The transesterification process is affected by reaction conditions, alcohol to oil molar ratio, type of alcohol, type and amount of catalysts, temperature and purity of reactants. Heterogeneous acid catalysts are quite efficient in promoting the…