High Performance Nanostructured Silicon Oxide Impedance Biosensor System with Online Noise Spectroscopy Analysis

2014 ◽  
Vol 1064 ◽  
pp. 191-196
Author(s):  
Nirmalya Samanta ◽  
Hrilina Ghosh
Keyword(s):  
Digital Signal Processor ◽  
High Performance ◽  
Silicon Oxide ◽  
Specific Antigen ◽  
Complex Mixture ◽  
Digital Signal ◽  
Noise Spectrum ◽  
Spectroscopy Analysis ◽  
Noise Spectroscopy ◽  
Biosensor System

In this paper, noise spectroscopy has been reported earlier as an efficient tool for enhancing the selectivity of biosensors and the analysis was carried out by desktop spectrum analyzer. There were no reports, however, on the efficacy of this method in complex mixture. We have performed here for the first time, noise spectroscopy analysis on complex mixture of food toxin samples and observed that the first cut-off frequencies are indicative of the fact whether the solution has only specific antigen, mixture of specific and nonspecific antigen or no specific antigen at all. To realize a portable immunosensor, we have developed an electronic interface using digital signal processor (DSP) chip of Microchip Technology which has the embedded Fast Fourier Transform (FFT) algorithm for computation of noise spectrum. The entire system has been successfully demonstrated to detect 0.1 fg/ml aflatoxin B1 (AfB1) from a complex mixture with as high as 1000ng/ml non-specific toxins.

scholarly journals SHIL and DHIL Simulations of Nonlinear Control Methods Applied for Power Converters Using Embedded Systems

Electronics ◽  
2018 ◽  
Vol 7 (10) ◽  
pp. 241 ◽  
Author(s):  
Arthur Rosa ◽  
Matheus Silva ◽  
Marcos Campos ◽  
Renato Santana ◽  
Welbert Rodrigues ◽  
...  
Keyword(s):  
Embedded Systems ◽  
Nonlinear Control ◽  
Real Time ◽  
Digital Signal Processor ◽  
High Performance ◽  
Power Converters ◽  
Digital Signal ◽  
Simulation Method ◽  
Hardware In The Loop ◽  
Control Techniques

In this work, a new real-time Simulation method is designed for nonlinear control techniques applied to power converters. We propose two different implementations: in the first one (Single Hardware in The Loop: SHIL), both model and control laws are inserted in the same Digital Signal Processor (DSP), and in the second approach (Double Hardware in The Loop: DHIL), the equations are loaded in different embedded systems. With this methodology, linear and nonlinear control techniques can be designed and compared in a quick and cheap real-time realization of the proposed systems, ideal for both students and engineers who are interested in learning and validating converters performance. The methodology can be applied to buck, boost, buck-boost, flyback, SEPIC and 3-phase AC-DC boost converters showing that the new and high performance embedded systems can evaluate distinct nonlinear controllers. The approach is done using matlab-simulink over commodity Texas Instruments Digital Signal Processors (TI-DSPs). The main purpose is to demonstrate the feasibility of proposed real-time implementations without using expensive HIL systems such as Opal-RT and Typhoon-HL.

PARALLEL ALGORITHMS FOR ADAPTIVE MATCHED-FIELD PROCESSING ON DISTRIBUTED ARRAY SYSTEMS

2004 ◽  
Vol 12 (02) ◽  
pp. 149-174 ◽  
Author(s):  
KILSEOK CHO ◽  
ALAN D. GEORGE ◽  
RAJ SUBRAMANIYAN ◽  
KEONWOOK KIM
Keyword(s):  
Parallel Algorithms ◽  
Real Time ◽  
Digital Signal Processor ◽  
High Performance ◽  
Digital Signal ◽  
Minimum Variance ◽  
Adaptive Beamforming ◽  
Matched Field Processing ◽  
Minimum Variance Distortionless Response ◽  
Distributed Array

Matched-field processing (MFP) localizes sources more accurately than plane-wave beamforming by employing full-wave acoustic propagation models for the cluttered ocean environment. The minimum variance distortionless response MFP (MVDR–MFP) algorithm incorporates the MVDR technique into the MFP algorithm to enhance beamforming performance. Such an adaptive MFP algorithm involves intensive computational and memory requirements due to its complex acoustic model and environmental adaptation. The real-time implementation of adaptive MFP algorithms for large surveillance areas presents a serious computational challenge where high-performance embedded computing and parallel processing may be required to meet real-time constraints. In this paper, three parallel algorithms based on domain decomposition techniques are presented for the MVDR–MFP algorithm on distributed array systems. The parallel performance factors in terms of execution times, communication times, parallel efficiencies, and memory capacities are examined on three potential distributed systems including two types of digital signal processor arrays and a cluster of personal computers. The performance results demonstrate that these parallel algorithms provide a feasible solution for real-time, scalable, and cost-effective adaptive beamforming on embedded, distributed array systems.

scholarly journals Optimizing Convolution Neural Network on the TI C6678 multicore DSP

2018 ◽  
Vol 246 ◽  
pp. 03044 ◽  
Author(s):  
Guozhao Zeng ◽  
Xiao Hu ◽  
Yueyue Chen
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Image Processing ◽  
Deep Learning ◽  
Digital Signal Processor ◽  
High Performance ◽  
Digital Signal ◽  
Automatic Translation ◽  
Convolution Operation ◽  
Multicore Dsp

Convolutional Neural Networks (CNNs) have become the most advanced algorithms for deep learning. They are widely used in image processing, object detection and automatic translation. As the demand for CNNs continues to increase, the platforms on which they are deployed continue to expand. As an excellent low-power, high-performance, embedded solution, Digital Signal Processor (DSP) is used frequently in many key areas. This paper attempts to deploy the CNN to Texas Instruments (TI)’s TMS320C6678 multi-core DSP and optimize the main operations (convolution) to accommodate the DSP structure. The efficiency of the improved convolution operation has increased by tens of times.

Design of PMSM Position Servo System Based on Fuzzy Adaptive PI Control

2013 ◽  
Vol 706-708 ◽  
pp. 737-741 ◽  
Author(s):  
Hong Mei Shi ◽  
Zu Jun Yu
Keyword(s):  
Digital Signal Processor ◽  
High Performance ◽  
Permanent Magnet Synchronous Motor ◽  
Servo System ◽  
Experimental System ◽  
Digital Signal ◽  
Adaptive Controller ◽  
Speed Performance ◽  
Position Servo ◽  
Fuzzy Adaptive

A fuzzy adaptive PI controller for permanent magnet synchronous motor (PMSM) position servo system is proposed in this paper. Based on the analysis of PMSM mathematical model, the design of position loop controller is introduced in detail. To verify the effectiveness and accuracy of the fuzzy PI adaptive controller, an experimental system is designed using TMS320F2812 floating-point digital signal processor (DSP) as controller CPU and DR20A as integrated power drive module. The experimental results show that the designed AC position servo system has strong robustness, better speed performance and higher position precision, which can meet the requirements of high performance servo system.

scholarly journals Development of a High-Speed Digitizer to Time Resolve Nanosecond Fluorescence Pulses

2012 ◽  
Vol 10 (2) ◽  
Author(s):  
E. Moreno-García ◽  
R. Galicia-Mejía ◽  
D. Jiménez-Olarte ◽  
J. M. de la Rosa Vázquez ◽  
S. Stolik-Isakina
Keyword(s):  
Time Domain ◽  
Digital Signal Processor ◽  
High Speed ◽  
High Performance ◽  
Input Pulse ◽  
Control Program ◽  
Sampling Technique ◽  
Digital Signal ◽  
Time Resolved ◽  
The Time Domain

The development of a high-speed digitizer system to measure time-domain voltage pulses in nanoseconds range is presented in this work. The digitizer design includes a high performance digital signal processor, a high-bandwidth analog-to-digital converter of flash-type, a set of delay lines, and a computer to achieve the time-domain measurements. A program running on the processor applies a time-equivalent sampling technique to acquire the input pulse. The processor communicates with the computer via a serial port RS-232 to receive commands and to transmit data. A control program written in LabVIEW 7.1 starts an acquisition routine in the processor. The program reads data from processor point by point in each occurrence of the signal, and plots each point to recover the time-resolved input pulse after n occurrences. The developed prototype is applied to measure fluorescence pulses from a homemade spectrometer. For this application, the LabVIEW program was improved to control the spectrometer, and to register and plot time-resolved fluorescence pulses produced by a substance. The developed digitizer has 750 MHz of analog input bandwidth, and it is able to resolve 2 ns rise-time pulses with 150 ps of resolution and a temporal error of 2.6 percent.

scholarly journals Design of Area Efficent 32 Bit Arithmetic and Logic Unit (ALU) for DSP Processors

2019 ◽  
Vol 8 (6S3) ◽  
pp. 1270-1278
Keyword(s):  
Digital Signal Processor ◽  
High Performance ◽  
Design Procedure ◽  
Large Data ◽  
Digital Signal ◽  
Cmos Technology ◽  
Improved Performance ◽  
Dsp Processors ◽  
Low Complex ◽  
Bitwise Operations

Almost every electronic gadget contains the Digital signal processor (DSP) unit for the purpose of computations, whose role couldn’t be specified with smaller words. Gadget’s performance, efficiency and the importance could be measured with how best the specifications of the processors are. Arithmetic and Logical Unit (ALU) is the key circuit for any DSP processors, where large data computations can be performed. Hence, the ALUs design should be include high performance and large data handling capacity. An ALU is a digital electronic circuit that performs arithmetic and bitwise operations on integer binary numbers. The conventional ALU designs, design complexity rate proportionally increases with the performance demand. In this paper, an attempt has been given to design a low complex ALU with improved performance. Sub circuits designs comprise with new approaches to make the simple designs for higher performance of ALU. A 32 bit ALU design procedure has been demonstrated in this paper. For design, 90 nm CMOS technology and CADENCE virtuoso tools used.

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