scholarly journals Resolving longitudinal amplitude and phase information of two continuous data streams for high-speed and real-time processing

2009 ◽  
Vol 7 ◽  
pp. 133-137 ◽  
Author(s):  
A. Guntoro ◽  
M. Glesner
Keyword(s):  
Data Streams ◽  
Data Stream ◽  
High Speed ◽  
Hardware Implementation ◽  
Software Implementation ◽  
Phase Detector ◽  
Continuous Data ◽  
Process Data ◽  
Real Time Processing ◽  
High Speed Data

Abstract. Although there is an increase of performance in DSPs, due to its nature of execution a DSP could not perform high-speed data processing on a continuous data stream. In this paper we discuss the hardware implementation of the amplitude and phase detector and the validation block on a FPGA. Contrary to the software implementation which can only process data stream as high as 1.5 MHz, the hardware approach is 225 times faster and introduces much less latency.

Real-Time Processing for High Speed Data Stream over Large Scale Data

2012 ◽  
Vol 35 (3) ◽  
pp. 477-490 ◽  
Author(s):  
Kai-Yuan QI ◽  
Zhuo-Feng ZHAO ◽  
Jun FANG ◽  
Qiang MA
Keyword(s):  
Real Time ◽  
Data Stream ◽  
High Speed ◽  
Large Scale ◽  
Real Time Processing ◽  
Time Processing ◽  
Large Scale Data ◽  
High Speed Data ◽  
Scale Data

scholarly journals Data Stream Classification Based on the Gamma Classifier

2015 ◽  
Vol 2015 ◽  
pp. 1-17 ◽  
Author(s):  
Abril Valeria Uriarte-Arcia ◽  
Itzamá López-Yáñez ◽  
Cornelio Yáñez-Márquez ◽  
João Gama ◽  
Oscar Camacho-Nieto
Keyword(s):  
Data Streams ◽  
Time Management ◽  
Data Stream ◽  
High Speed ◽  
Concept Drift ◽  
Synthetic Data ◽  
Continuous Data ◽  
Data Generation ◽  
Underlying Distribution ◽  
Data Stream Classification

The ever increasing data generation confronts us with the problem of handling online massive amounts of information. One of the biggest challenges is how to extract valuable information from these massive continuous data streams during single scanning. In a data stream context, data arrive continuously at high speed; therefore the algorithms developed to address this context must be efficient regarding memory and time management and capable of detecting changes over time in the underlying distribution that generated the data. This work describes a novel method for the task of pattern classification over a continuous data stream based on an associative model. The proposed method is based on the Gamma classifier, which is inspired by the Alpha-Beta associative memories, which are both supervised pattern recognition models. The proposed method is capable of handling the space and time constrain inherent to data stream scenarios. The Data Streaming Gamma classifier (DS-Gamma classifier) implements a sliding window approach to provide concept drift detection and a forgetting mechanism. In order to test the classifier, several experiments were performed using different data stream scenarios with real and synthetic data streams. The experimental results show that the method exhibits competitive performance when compared to other state-of-the-art algorithms.

Design of the Control Circuit Based on FPGA for the Underwater Trash Detection System

2011 ◽  
Vol 201-203 ◽  
pp. 2414-2418
Author(s):  
Guo Ku Zhao ◽  
Qi Zhang
Keyword(s):  
High Speed ◽  
Analog Circuit ◽  
Detection System ◽  
Control Circuit ◽  
Echo Signal ◽  
Process Data ◽  
Ultrasonic Detection ◽  
Distance Information ◽  
High Speed Data ◽  
System Power

For the detection of underwater trashes, the ultrasonic detection system is a necessary deceive. In the traditional ultrasonic detection system, echo signal is generally processed by analog circuit, and only the distance information is obtained. In order to determine the distance and material of target, the amplitude of echo wave also need to be extracted, and FPGA is employed to control high-speed AD and process data. The design of control circuit based on FPGA is presented here. The control circuit includes modules of clock, high-speed data processing, communication and transmitting control. On the basis of the system design, simulation, implementation, the system experiments are completed. The results show: the functions of the control circuit based on FPGA are implemented correctly, but the system power consumption needs to be reduced more.

Sign in / Sign up

Export Citation Format

Share Document