scholarly journals An FPGA-based single-precision floating-point 2048-points FFT implementation based on adaptive angle recoding CORDIC

2017 ◽  
Vol 1 (T4) ◽  
pp. 172-179
Author(s):  
Quynh Thi Nhu Truong ◽  
Thao Thi Phuong Vo ◽  
Thuc Trong Hoang
Keyword(s):  
Mean Square Error ◽  
Floating Point ◽  
Cordic Algorithm ◽  
Mean Square ◽  
Maximum Frequency ◽  
Single Precision ◽  
Fpga Chip

In this paper, an FPGA-based single-precision floating-point 2048-point FFT implementation is proposed, based on an adaptive angle recoding CORDIC algorithm. The design is built and verified on Altera Stratix V FPGA chip. The implementation had 102.55 MHz maximum frequency, throughput result of 8424.382 FFTs/s, and resources utilization of 76,282 ALUTs and 15,687 registers. The accuracy results were 5.889E-06 (Mean-Square-Error (MSE).

scholarly journals An efficient floating-point FFT twiddle factor implementation based on adaptive angle recoding CORDIC algorithm

2017 ◽  
Vol 1 (T4) ◽  
pp. 187-196
Author(s):  
Thao Thi Phuong Vo ◽  
Quynh Thi Nhu Truong ◽  
Thuc Trong Hoang ◽  
Hung Duc Le
Keyword(s):  
Maximum Error ◽  
The Other ◽  
Floating Point ◽  
Cordic Algorithm ◽  
Mean Square ◽  
Maximum Frequency ◽  
Single Precision ◽  
Standard Cells ◽  
Twiddle Factor ◽  
Fpga Chip

In this paper, a single-precision floating-point FFT twiddle factor (TF) implementation is proposed. The architecture is based on the Adaptive Angle Recoding CORDIC (AARC) algorithm. The TF design was built and verified on Altera Stratix IV FPGA chip and 65nm SOTB synthesis. The FPGA implementation had 103.9 MHz maximum frequency, throughput result of 16.966 Mega-Sample per second (MSps), and resources utilization of 7.747 ALUTs and 625 registers. On the other hand, the SOTB synthesis has 16.858 standard cells on an area of 298x291 μm2, 166 MHz maximum frequency, and the speed of 27.107 MSps. The accuracy results were 1.133E-10 Mean-Square-Error (MSE) and about 26 part-per-million (ppm) maximum error.

The Bordeaux Automatic Meridian Circle

1978 ◽  
Vol 48 ◽  
pp. 227-228
Author(s):  
Y. Requième
Keyword(s):  
Mean Square Error ◽  
Mean Square ◽  
Meridian Circle ◽  
The Mean ◽  
Full Automation

In spite of important delays in the initial planning, the full automation of the Bordeaux meridian circle is progressing well and will be ready for regular observations by the middle of the next year. It is expected that the mean square error for one observation will be about ±0.”10 in the two coordinates for declinations up to 87°.

Investigation of Accuracy of a Calibrated Estimator of a Ratio by Modelling

2005 ◽  
Vol 10 (4) ◽  
pp. 333-342
Author(s):  
V. Chadyšas ◽  
D. Krapavickaitė
Keyword(s):  
Mean Square Error ◽  
Taylor Series ◽  
Random Sampling ◽  
Finite Population ◽  
Taylor Series Expansion ◽  
Simple Random Sampling ◽  
Population Parameter ◽  
Mean Square ◽  
Parameter Ratio ◽  
Using Data

Estimator of finite population parameter – ratio of totals of two variables – is investigated by modelling in the case of simple random sampling. Traditional estimator of the ratio is compared with the calibrated estimator of the ratio introduced by Plikusas [1]. The Taylor series expansion of the estimators are used for the expressions of approximate biases and approximate variances [2]. Some estimator of bias is introduced in this paper. Using data of artificial population the accuracy of two estimators of the ratio is compared by modelling. Dependence of the estimates of mean square error of the estimators of the ratio on the correlation coefficient of variables which are used in the numerator and denominator, is also shown in the modelling.

Performance analysis of global local mean square error criterion of stochastic linearization for nonlinear oscillator

2019 ◽  
Author(s):  
Nguyen Cao Thang ◽  
Luu Xuan Hung
Keyword(s):  
Performance Analysis ◽  
Mean Square Error ◽  
Nonlinear Oscillators ◽  
Degree Of Freedom ◽  
Equivalent Linearization ◽  
Mean Square ◽  
Error Criterion ◽  
Stochastic Linearization ◽  
Local Mean ◽  
Mean Square Error Criterion

The paper presents a performance analysis of global-local mean square error criterion of stochastic linearization for some nonlinear oscillators. This criterion of stochastic linearization for nonlinear oscillators bases on dual conception to the local mean square error criterion (LOMSEC). The algorithm is generally built to multi degree of freedom (MDOF) nonlinear oscillators. Then, the performance analysis is carried out for two applications which comprise a rolling ship oscillation and two degree of freedom one. The improvement on accuracy of the proposed criterion has been shown in comparison with the conventional Gaussian equivalent linearization (GEL).

Detection of Biomedical Images by Using Bio-inspired Artificial Intelligent

2020 ◽  
Vol 38 (2A) ◽  
pp. 255-264
Author(s):  
Hanan A. R. Akkar ◽  
Sameem A. Salman
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Mean Square Error ◽  
Average Rate ◽  
Mean Square ◽  
Performance Measurements ◽  
Artificial Intelligent ◽  
Average Mean Square Error ◽  
Artificial Neural ◽  
Artificial Neural Network Ann

Computer vision and image processing are extremely necessary for medical pictures analysis. During this paper, a method of Bio-inspired Artificial Intelligent (AI) optimization supported by an artificial neural network (ANN) has been widely used to detect pictures of skin carcinoma. A Moth Flame Optimization (MFO) is utilized to educate the artificial neural network (ANN). A different feature is an extract to train the classifier. The comparison has been formed with the projected sample and two Artificial Intelligent optimizations, primarily based on classifier especially with, ANN-ACO (ANN training with Ant Colony Optimization (ACO)) and ANN-PSO (training ANN with Particle Swarm Optimization (PSO)). The results were assessed using a variety of overall performance measurements to measure indicators such as Average Rate of Detection (ARD), Average Mean Square error (AMSTR) obtained from training, Average Mean Square error (AMSTE) obtained for testing the trained network, the Average Effective Processing Time (AEPT) in seconds, and the Average Effective Iteration Number (AEIN). Experimental results clearly show the superiority of the proposed (ANN-MFO) model with different features.

Performance enhancement of Echo Cancellation Using a Combination of Partial Update ( PU) Methods and New Variable Length LMS (NVLLMS) Algorithm

2018 ◽  
Vol 24 (5) ◽  
pp. 66
Author(s):  
Thamer M. Jamel ◽  
Faez Fawzi Hammood
Keyword(s):  
Mean Square Error ◽  
Return Loss ◽  
Performance Enhancement ◽  
Variable Length ◽  
Echo Cancellation ◽  
Convergence Time ◽  
Length Variation ◽  
Mean Square ◽  
Step Size ◽  
Echo Return Loss Enhancement

In this paper, several combination algorithms between Partial Update LMS (PU LMS) methods and previously proposed algorithm (New Variable Length LMS (NVLLMS)) have been developed. Then, the new sets of proposed algorithms were applied to an Acoustic Echo Cancellation system (AEC) in order to decrease the filter coefficients, decrease the convergence time, and enhance its performance in terms of Mean Square Error (MSE) and Echo Return Loss Enhancement (ERLE). These proposed algorithms will use the Echo Return Loss Enhancement (ERLE) to control the operation of filter's coefficient length variation. In addition, the time-varying step size is used.The total number of coefficients required was reduced by about 18% , 10% , 6%, and 16% using Periodic, Sequential, Stochastic, and M-max PU NVLLMS algorithms respectively, compared to that used by a full update method which  is very important, especially in the application of mobile communication since the power consumption must be considered. In addition, the average ERLE and average Mean Square Error (MSE) for M-max PU NVLLMS are better than other proposed algorithms.  

Prediksi Daya Panel Surya Kapasitas 50 Wp Menggunakan Model Regresi Linier Majemuk

2020 ◽  
Vol 10 (2) ◽  
Author(s):  
Radian Indra Mukromin ◽  
Muhammad Khamim Asy'ari
Keyword(s):  
Mean Square Error ◽  
Mean Square

Sistem monitoring daya listrik pada panel surya penting dilakukan. Hal ini disebabkan daya listrik panel surya dapat mempengaruhi performansi pengisian baterai dan keandalan dari panel surya.  Sifat stokastik dari temperatur panel surya dan iradiasi surya mengakibatkan fluktuasi daya listrik, sehingga diperlukan sistem prediksi daya panel surya. Sistem prediksi dapat dirancang untuk mendapatkan model prediksi daya panel surya secara matematik menggunakan model regresi linier majemuk. Model dibangun untuk sistem prediksi dengan menggunakan data latih dari keluaran panel surya. Variasi yang diberikan adalah jenis variabel masukan untuk membangun model. Variabel masukan model terdiri dari temperatur panel surya, iradiasi surya, dan kombinasi dari keduanya. Pengujian data dilakukan dengan menggunakan uji korelasi majemuk, uji signifikasi regresi linier majemuk, dan uji signifikasi koefisien regresi. Hasil perancangan sistem prediksi terbaik adalah kombinasi temperatur panel surya dan iradiasi surya sebagai variabel masukan. Nilai MSE(mean square error) terkecil sebesar 9,83 untuk data latih dan 22,73 untuk data uji.

Cancelable Biometric System for face Based on linear minimum mean square error Model.

2019 ◽  
Vol 28 (1) ◽  
pp. 145-152
Author(s):  
Abd El-aziz Ebrahim Hsaneen ◽  
EL-Sayed M. El-Rabaei ◽  
Moawad I. Dessouky ◽  
Ghada El-bamby ◽  
Fathi E. Abd El-Samie ◽  
...  
Keyword(s):  
Mean Square Error ◽  
Minimum Mean Square Error ◽  
Error Model ◽  
Mean Square ◽  
Biometric System
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