Performance of high-bandwidth TRABOL protocol for radar data streaming

2006 ◽  
Author(s):  
Ashley Trimmer ◽  
Tarun Banka ◽  
Panho Lee ◽  
Anura P. Jayasumana ◽  
V. Chandrasekar
Keyword(s):  
Radar Data ◽  
Data Streaming ◽  
High Bandwidth

scholarly journals An integrated brain-machine interface platform with thousands of channels

2019 ◽  
Author(s):  
Elon Musk ◽  
Keyword(s):  
Electrode Array ◽  
Brain Regions ◽  
White Paper ◽  
Data Streaming ◽  
Flexible Electrode ◽  
Implanted Electrodes ◽  
High Bandwidth ◽  
Machine Interface ◽  
The Brain ◽  
Neurosurgical Robot

AbstractBrain-machine interfaces (BMIs) hold promise for the restoration of sensory and motor function and the treatment of neurological disorders, but clinical BMIs have not yet been widely adopted, in part because modest channel counts have limited their potential. In this white paper, we describe Neuralink’s first steps toward a scalable high-bandwidth BMI system. We have built arrays of small and flexible electrode “threads”, with as many as 3,072 electrodes per array distributed across 96 threads. We have also built a neurosurgical robot capable of inserting six threads (192 electrodes) per minute. Each thread can be individually inserted into the brain with micron precision for avoidance of surface vasculature and targeting specific brain regions. The electrode array is packaged into a small implantable device that contains custom chips for low-power on-board amplification and digitization: the package for 3,072 channels occupies less than (23 × 18.5 × 2) mm3. A single USB-C cable provides full-bandwidth data streaming from the device, recording from all channels simultaneously. This system has achieved a spiking yield of up to 70% in chronically implanted electrodes. Neuralink’s approach to BMI has unprecedented packaging density and scalability in a clinically relevant package.

scholarly journals Virtual CSU-CHILL Radar: The VCHILL

2005 ◽  
Vol 22 (7) ◽  
pp. 979-987 ◽  
Author(s):  
V. Chandrasekar ◽  
Yoong-Goog Cho ◽  
D. Brunkow ◽  
A. Jayasumana
Keyword(s):  
Real Time ◽  
Radar Data ◽  
Graphic User Interface ◽  
Research Experience ◽  
Time Data ◽  
System Architectures ◽  
Colorado State University ◽  
Radar Images ◽  
Atmospheric Remote Sensing ◽  
High Bandwidth

Abstract The Virtual CHILL (VCHILL) system makes it possible to transfer the educational and research experience of the Colorado State University dual polarization radar to remote locations over the Internet. The VCHILL operation includes remote control of radar and display of radar images, as well as the ability to locally process high-bandwidth radar data transferred over data networks. The low-bandwidth VCHILL operation allows the distant users to access the archived and real-time data estimated at the radar site and simultaneously display them on their local systems. A parallel receiver was developed exclusively for the high-bandwidth VCHILL. End-system architectures were designed to accommodate the demands of the high-bandwidth VCHILL operations in real time. A graphic user interface was also developed with the objective of easy installation and usage at various end-user institutions. The VCHILL not only expands the education experience provided by the radar system, but also stimulates the development of innovative research applications for atmospheric remote sensing. The VCHILL is being used by several universities for research and education.

scholarly journals An Integrated Brain-Machine Interface Platform With Thousands of Channels

10.2196/16194 ◽  
2019 ◽  
Vol 21 (10) ◽  
pp. e16194 ◽  
Author(s):  
Elon Musk ◽  
Keyword(s):  
Electrode Array ◽  
Brain Regions ◽  
White Paper ◽  
Brain Machine Interface ◽  
Data Streaming ◽  
Brain Machine Interfaces ◽  
Implanted Electrodes ◽  
High Bandwidth ◽  
Machine Interface ◽  
Neurosurgical Robot

Brain-machine interfaces hold promise for the restoration of sensory and motor function and the treatment of neurological disorders, but clinical brain-machine interfaces have not yet been widely adopted, in part, because modest channel counts have limited their potential. In this white paper, we describe Neuralink’s first steps toward a scalable high-bandwidth brain-machine interface system. We have built arrays of small and flexible electrode “threads,” with as many as 3072 electrodes per array distributed across 96 threads. We have also built a neurosurgical robot capable of inserting six threads (192 electrodes) per minute. Each thread can be individually inserted into the brain with micron precision for avoidance of surface vasculature and targeting specific brain regions. The electrode array is packaged into a small implantable device that contains custom chips for low-power on-board amplification and digitization: The package for 3072 channels occupies less than 23×18.5×2 mm3. A single USB-C cable provides full-bandwidth data streaming from the device, recording from all channels simultaneously. This system has achieved a spiking yield of up to 70% in chronically implanted electrodes. Neuralink’s approach to brain-machine interface has unprecedented packaging density and scalability in a clinically relevant package.

scholarly journals An Integrated Brain-Machine Interface Platform With Thousands of Channels (Preprint)

2019 ◽  
Author(s):  
Elon Musk ◽  
Keyword(s):  
Electrode Array ◽  
Brain Regions ◽  
White Paper ◽  
Data Streaming ◽  
Flexible Electrode ◽  
Implanted Electrodes ◽  
High Bandwidth ◽  
Machine Interface ◽  
The Brain ◽  
Neurosurgical Robot

UNSTRUCTURED Brain-machine interfaces (BMIs) hold promise for the restoration of sensory and motor function and the treatment of neurological disorders, but clinical BMIs have not yet been widely adopted, in part, because modest channel counts have limited their potential. In this white paper, we describe Neuralink’s first steps toward a scalable high-bandwidth BMI system. We have built arrays of small and flexible electrode “threads,” with as many as 3072 electrodes per array distributed across 96 threads. We have also built a neurosurgical robot capable of inserting six threads (192 electrodes) per minute. Each thread can be individually inserted into the brain with micron precision for avoidance of surface vasculature and targeting specific brain regions. The electrode array is packaged into a small implantable device that contains custom chips for low-power on-board amplification and digitization: The package for 3072 channels occupies less than 23×18.5×2 mm3. A single USB-C cable provides full-bandwidth data streaming from the device, recording from all channels simultaneously. This system has achieved a spiking yield of up to 70% in chronically implanted electrodes. Neuralink’s approach to BMI has unprecedented packaging density and scalability in a clinically relevant package.

scholarly journals Complicity of High-End SOC-FPGA’s for Data Centers

2021 ◽  
Vol 9 (6) ◽  
pp. 6-10
Author(s):  
Anil Kumar Retikal
Keyword(s):  
Data Analytics ◽  
Data Centers ◽  
Big Data Analytics ◽  
Low Latency ◽  
Data Streaming ◽  
Power Efficient ◽  
Efficient Data ◽  
High Bandwidth ◽  
Streaming Big Data

As the network traffic increasing significantly due to increase in Data streaming, Big Data Analytics, Cloud Computing, Increasing the load on Data Centers, Which leads to demand for high computational capabilities, low latency, high-bandwidth, power efficient data accelerators. As Re-Configurability of FPGA’s are more flexible for developing customized applications, so the FPGA hardware based data accelerators are the potential devices to achieve low latency and power efficient requirements. The modern FPGA’s are coming up with the embedded communication hard IP’s like PCIe, Ethernet, & DDR based memory controllers, which makes easy for the deployment of network attached FPGA’s in data centers. This paper presents the role of FPGA’s in datacenters and analysis of high-end FPGA’s by various vendors, which are suitable for deployment in data centers.

Data management of sensor signals for high bandwidth data streaming to the cloud

2016 ◽  
Author(s):  
Theodoros Soultanopoulos ◽  
Stelios Sotiriadis ◽  
Euripides G. M. Petrakis ◽  
Cristiana Amza
Keyword(s):  
Data Management ◽  
Data Streaming ◽  
High Bandwidth ◽  
Sensor Signals

A Review on Big Data Analytics in Business

2018 ◽  
pp. 210-214
Author(s):  
Manbir Sandhu ◽  
Purnima, Anuradha Saini
Keyword(s):  
Big Data ◽  
Big Data Analytics ◽  
Smart Devices ◽  
Data Streaming ◽  
Huge Amount ◽  
Business Units ◽  
Enormous Amount ◽  
Tools And Techniques ◽  
Heath Care ◽  
Data Analytic

Big data is a fast-growing technology that has the scope to mine huge amount of data to be used in various analytic applications. With large amount of data streaming in from a myriad of sources: social media, online transactions and ubiquity of smart devices, Big Data is practically garnering attention across all stakeholders from academics, banking, government, heath care, manufacturing and retail. Big Data refers to an enormous amount of data generated from disparate sources along with data analytic techniques to examine this voluminous data for predictive trends and patterns, to exploit new growth opportunities, to gain insight, to make informed decisions and optimize processes. Data-driven decision making is the essence of business establishments. The explosive growth of data is steering the business units to tap the potential of Big Data to achieve fueling growth and to achieve a cutting edge over their competitors. The overwhelming generation of data brings with it, its share of concerns. This paper discusses the concept of Big Data, its characteristics, the tools and techniques deployed by organizations to harness the power of Big Data and the daunting issues that hinder the adoption of Business Intelligence in Big Data strategies in organizations.

Potentialities of the comparison of «Sich-1M» side looking radar data and foreign satellite information

2004 ◽  
Vol 10 (2-3) ◽  
pp. 93-100
Author(s):  
V.V. Malynovskyi ◽  
◽  
V.P. Zubko ◽  
V.V. Pustovoitenko ◽  
◽  
...  
Keyword(s):  
Radar Data ◽  
Satellite Information ◽  
Side Looking Radar
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