Implementation of the Hartley-Transform-Based Block LMS Algorithm

1993 ◽  
Author(s):  
Tokunbo Ogunfunmi
Keyword(s):  
Digital Signal Processor ◽  
Adaptive Algorithm ◽  
Interference Cancellation ◽  
Digital Signal ◽  
Cost Effective ◽  
Lms Algorithm ◽  
Transform Domain ◽  
Least Mean Square ◽  
Hartley Transform ◽  
The Time Domain

Abstract This paper presents a cost-effective The Frequency-domain Least-Mean-Square (FLMS) adaptive algorithm (or more generally the Transform-domain LMS adaptive algorithm) [12], [13] has mainly two advantages over the conventional LMS algorithm [19]. The first is that it overcomes the slow convergence of the LMS algorithm by orthogonalizing the input (thereby performing better than the LMS for correlated input signals) and the second advantage is that it can be used for implementing the time-domain Block LMS (BLMS) algorithms as well [18]. The Hartley transform is a newly introduced real-to-real transform that is a suitable replacement for the complex Fourier transform [1] and [2] in several adaptive filtering applications such as adaptive interference cancellation that has wide applicability to problems in telecommunications, biomedical engineering, etc. The realization of the Transform-domain BLMS adaptive algorithm based on the Discrete Hartley Transforms (DHT) and its implementation on the TMS320C30 digital signal processor chip is described.

Convergence analysis of Bessel beamformer and its comparison with LMS in adaptive array system

2015 ◽  
Vol 34 (3) ◽  
pp. 952-961 ◽  
Author(s):  
M. Yasin ◽  
Pervez Akhtar
Keyword(s):  
Theoretical Model ◽  
Convergence Analysis ◽  
Digital Signal Processor ◽  
Wiener Filter ◽  
Digital Signal ◽  
Lms Algorithm ◽  
Mean Square ◽  
Least Mean Square ◽  
Content Type ◽  
Convergence Performance

Purpose – The purpose of this paper is to analyze the convergence performance of Bessel beamformer, based on the design steps of least mean square (LMS) algorithm, can be named as Bessel LMS (BLMS) algorithm. Its performance is compared in adaptive environment with LMS in terms of two important performance parameters, namely; convergence and mean square error. The proposed BLMS algorithm is implemented on digital signal processor along with antenna array to make it smart in wireless sensor networks. Design/methodology/approach – Convergence analysis is theoretically developed and verified through MatLab Software. Findings – Theoretical model is verified through simulation and its results are shown in the provided table. Originality/value – The theoretical model can obtain validation from well-known result of Wiener filter theory through principle of orthogonality.

scholarly journals A flexible user-interface for audiovisual presentation and interactive control in neurobehavioral experiments

F1000Research ◽  
2013 ◽  
Vol 2 ◽  
pp. 20
Author(s):  
Christopher T Noto ◽  
Suleman Mazhar ◽  
James Gnadt ◽  
Jagmeet S Kanwal
Keyword(s):  
User Interface ◽  
Data Acquisition ◽  
Digital Signal Processor ◽  
Digital Signal ◽  
Stimulus Presentation ◽  
Cost Effective ◽  
Level Control ◽  
Interactive Control ◽  
High Level ◽  
Behavioral Monitoring

A major problem facing behavioral neuroscientists is a lack of unified, vendor-distributed data acquisition systems that allow stimulus presentation and behavioral monitoring while recording neural activity. Numerous systems perform one of these tasks well independently, but to our knowledge, a useful package with a straightforward user interface does not exist. Here we describe the development of a flexible, script-based user interface that enables customization for real-time stimulus presentation, behavioral monitoring and data acquisition. The experimental design can also incorporate neural microstimulation paradigms. We used this interface to deliver multimodal, auditory and visual (images or video) stimuli to a nonhuman primate and acquire single-unit data. Our design is cost-effective and works well with commercially available hardware and software. Our design incorporates a script, providing high-level control of data acquisition via a sequencer running on a digital signal processor to enable behaviorally triggered control of the presentation of visual and auditory stimuli. Our experiments were conducted in combination with eye-tracking hardware. The script, however, is designed to be broadly useful to neuroscientists who may want to deliver stimuli of different modalities using any animal model.

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.

Position Sensorless Control for PMBLDC Motor Drive Using Digital Signal Processor

2016 ◽  
Vol 25 (07) ◽  
pp. 1650077 ◽  
Author(s):  
Sachin Singh ◽  
Sanjeev Singh
Keyword(s):  
Digital Signal Processor ◽  
Sensorless Control ◽  
Digital Signal ◽  
Cost Effective ◽  
Open Loop ◽  
Brushless Dc Motors ◽  
Wide Range ◽  
Permanent Magnet Brushless Dc ◽  
Signal Processor ◽  
Position Sensorless

This paper presents a complete position sensorless control scheme for permanent magnet brushless DC motors (PMBLDCMs) using back-EMF sensing method. The controller is designed in such a way that it provides smooth shifting from open-loop speed-up mode to back-EMF sensing mode at any speed, especially at very low speeds, i.e., less than 2% of the rated speed. The proposed scheme is a simple and cost effective implementation of back-EMF sensing method, which does not require any filtering or phase shift to generate commutation pulses. The proposed controller is designed and modeled for a PMBLDCM rated at 4600[Formula: see text]rpm, 310[Formula: see text]V and 2.2[Formula: see text]N[Formula: see text]m torque and its performance is simulated in MATLAB/SIMULINK environment. The obtained simulation results are validated on a prototype developed in the lab using a digital signal processor (DSP) namely TI 2812 DSP in a wide range of speeds in position sensorless mode.

ANALYSIS OF THE TRANSFORM DOMAIN LMS ALGORITHM WITH INSUFFICIENT LENGTH ADAPTIVE FILTER

2005 ◽  
Vol 14 (03) ◽  
pp. 469-481 ◽  
Author(s):  
K. MAYYAS
Keyword(s):  
Adaptive Filter ◽  
Adaptive Algorithm ◽  
Lms Algorithm ◽  
Response Analysis ◽  
Transform Domain ◽  
Practical Applications ◽  
Mean Square Convergence ◽  
Gaussian Input ◽  
Unknown System ◽  
Theoretical Results

Though, in most practical applications, the length of the adaptive filter is less than that of the unknown system impulse response, analysis of adaptive filtering algorithms almost always assumed a sufficient length adaptive filter whose length is equal to that of unknown system. Theoretical results on the sufficient length adaptive algorithm do not necessarily apply to the realistic insufficient length case and, therefore, it becomes extremely desirable for practical purposes that we quantify the statistical behavior of the insufficient length adaptive algorithm. In this paper, we analyze the popular Transform Domain LMS (TDLMS) algorithm with insufficient length adaptive filter for Gaussian input data and using the common independence assumption. Analysis yields exact theoretical expressions that describe the mean and mean-square convergence of the algorithm, which lead to a better understanding to the performance properties of the insufficient length TDLMS adaptive algorithm. Simulation experiments illustrate the accuracy of the theoretical results in predicting the convergence behavior of the algorithm.

DIRECT-SEQUENCE SPREAD-SPECTRUM WITH TRANSFORM DOMAIN INTERFERENCE SUPPRESSION

1995 ◽  
Vol 05 (02) ◽  
pp. 167-179 ◽  
Author(s):  
TAKIS KASPARIS ◽  
MICHAEL GEORGIOPOULOS ◽  
QURBAN MEMON
Keyword(s):  
Spread Spectrum ◽  
Interference Suppression ◽  
Direct Sequence Spread Spectrum ◽  
Lms Algorithm ◽  
Transform Domain ◽  
Direct Sequence ◽  
New Techniques ◽  
Using Data ◽  
Notch Filtering ◽  
The Time Domain

The performance of a direct-sequence spread-spectrum (DS-SS) receiver employing new techniques for multiple non-stationary interference suppression is presented. These techniques are based on transform domain order statistics and they selectively suppress spectral components that are sufficiently large and narrow. Other important advantages are also discussed. The bit error rate performance is determined by Monte-Carlo simulations and it is compared to the performance of fixed notch filtering and of the well-known LMS algorithm. The effect of using data windowing is examined, and results with single-tone, narrow-band, stationary, non-stationary and multiple interference are presented. A comparison of the amount of computation required by the proposed transform domain approach to that of the time-domain LMS algorithm is also presented.

Simulation and Comparison of Adaptive Detection Algorithm

2011 ◽  
Vol 130-134 ◽  
pp. 2692-2695 ◽  
Author(s):  
Yun Liang Wang ◽  
Guo Cun Li
Keyword(s):  
Adaptive Algorithm ◽  
Detection Algorithm ◽  
Lms Algorithm ◽  
Detection Methods ◽  
Least Mean Square ◽  
Harmonic Detection ◽  
Harmonic Current ◽  
Power Filter ◽  
Simulation Based ◽  
Current Detection

The active power filter has two key link for harmonic current detection and respectively compensation current tracking. This article mainly aims at harmonic current detection link. Firstly, Analysis adaptive harmonic detection methods, then based on over to LMS (Least Mean Square) adaptive algorithm as the research object, in discussing the adaptive algorithm criteria. By comparing several simulation-based LMS algorithm to achieve the results of the filter,analyse the causes of the results.

scholarly journals A flexible user-interface for audiovisual presentation and interactive control in neurobehavioral experiments

F1000Research ◽  
2014 ◽  
Vol 2 ◽  
pp. 20
Author(s):  
Christopher T Noto ◽  
Suleman Mazhar ◽  
James Gnadt ◽  
Jagmeet S Kanwal
Keyword(s):  
User Interface ◽  
Data Acquisition ◽  
Digital Signal Processor ◽  
Digital Signal ◽  
Stimulus Presentation ◽  
Cost Effective ◽  
Level Control ◽  
Interactive Control ◽  
High Level ◽  
Behavioral Monitoring

A major problem facing behavioral neuroscientists is a lack of unified, vendor-distributed data acquisition systems that allow stimulus presentation and behavioral monitoring while recording neural activity. Numerous systems perform one of these tasks well independently, but to our knowledge, a useful package with a straightforward user interface does not exist. Here we describe the development of a flexible, script-based user interface that enables customization for real-time stimulus presentation, behavioral monitoring and data acquisition. The experimental design can also incorporate neural microstimulation paradigms. We used this interface to deliver multimodal, auditory and visual (images or video) stimuli to a nonhuman primate and acquire single-unit data. Our design is cost-effective and works well with commercially available hardware and software. Our design incorporates a script, providing high-level control of data acquisition via a sequencer running on a digital signal processor to enable behaviorally triggered control of the presentation of visual and auditory stimuli. Our experiments were conducted in combination with eye-tracking hardware. The script, however, is designed to be broadly useful to neuroscientists who may want to deliver stimuli of different modalities using any animal model.

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