scholarly journals IDENTIFIKASI ASPEK GELOMBANG BUNYI KELUARAN ALAT MUSIK SASANDO TRADISIONAL DAN SASANDO ELEKTRIK

2020 ◽  
Vol 5 (2) ◽  
pp. 100-107
Author(s):  
Martince Aryani Jusuf Kaba ◽  
Ali Warsito ◽  
Laura A.S Lapono
Keyword(s):  
Fourier Transform ◽  
Data Processing ◽  
Fast Fourier Transform ◽  
Sound Wave ◽  
Musical Instruments ◽  
Original Sample ◽  
Intensity Noise ◽  
Sound Waves ◽  
The Subject ◽  
Frequency Intensity

ABSTRAK Telah dilakukan penelitian tentang identifikasi aspek gelombang bunyi alat musik sasando tradisional dan sasando elektrik. Subjek penelitian ini adalah bunyi alat musik sasando tradisional dan sasando elektrik yang bertipe sasando biola dengan jumlah dawai 32. Bunyi alat musik sasando direkam dengan mikrofon Havit Straight M-80 dan dianalisis menggunakan perangkat lunak Wavepad sound editor. Aspek gelombang bunyi ditentukan dengan menggunakan metode Fast Fourier Transform (FFT). Sampel original bunyi sasando tradisional dan sasando elektrik dengan rentang frekuensi dari 86 Hz sampai 1206 Hz dan 97 Hz sampai 1077 Hz. Rentang intensitas dari sasando tradisional dan sasando elektrik secara berturut-turut (-45,95398906) dB sampai (-12,38564365) dB dan (-33,44661942) dB sampai (-9,780729931) dB. Kemudian dengan perangkat lunak excel diperoleh grafik data bunyi sasando tradisional dan sasando elektrik berupa grafik intensitas, frekuensi dan noise. Setelah dilakukan filter terhadap sampel original bunyi sasando tradisional dan sasando elektrik, yang mempengaruhi kualitas gelombang bunyi adalah adalah rentang noise pada sampel bunyi  dari pengolahan data -2 dB sampai 0 dB dan -4,22  dB sampai -0,14 dB dengan persentase noise 0 % sampai 8,27 % dan 0,57 % sampai 22,76 %. Sebagian besar persentasi noise berpengaruh pada bunyi asli.   Kata Kunci: Sasando, sampel original, mikrofon Havit Straight M-80, Wavepad sound editor, metode Fast Fourier Transform (FFT), frekuensi, intensitas, noise.   ABSTRACT Research has been conducted on the identification of aspects of the sound waves of traditional Sasando musical instruments and Sasando electric. The subject of this research is the sound of traditional Sasando musical instruments and Sasando electric type of Sasando violin with 32 strings. The sounds of Sasando musical instruments were recorded with the Havit Straight M-80 microphone and analyzed using Wavepad sound editor software. Sound wave aspects are determined using the Fast Fourier Transform (FFT) method. Original samples of traditional Sasando sound and Sasando electric range in frequency from 86 Hz to 1206 Hz and 97 Hz to 1077 Hz. The intensity ranges from traditional Sasando and Sasando electric are (-45,95398906) dB to (-12,38564365) dB and (-33,44661942) dB to (-9,780729931) dB. Then with Excel software obtained data graphs of traditional Sasando sound and Sasando electric in the form of graphs of intensity, frequency and noise. After filtering the original samples of traditional Sasando sound and Sasando electric, what affects the sound wave quality is the range of noise in the sound sample from data processing of -2 dB to 0 dB and -4.22 dB to -0.14 dB with a percentage of noise 0 % to 8.27% and 0.57% to 22.76%. Most of the noise percentage affects the original sound. Keywords: Sasando, original sample, Havit Straight M-80 microphone, Wavepad sound editor, Fast Fourier Transform (FFT) method, frequency, intensity, noise.

scholarly journals PENGENALAN POLA SUARA MANUSIA BEREKSTENSI FILE WAV MENGGUNAKAN METODE FAST FOURIER TRANSFORM DAN BAYES

2018 ◽  
Vol 2 (1) ◽  
pp. 1 ◽  
Author(s):  
Nurlia Apriani ◽  
Rita Wiryasaputra ◽  
Lastri Widya Astuti
Keyword(s):  
Fourier Transform ◽  
Fast Fourier Transform ◽  
Test Data ◽  
Sound Wave ◽  
Sound Level ◽  
Sound Waves ◽  
Bayes Method ◽  
Transform Method ◽  
Human Voice ◽  
Accuracy Result

The human voice is a very unique sound wave. That's because every human being has a different kind of sound wave. The fundamental difference in human voice is high the low the sound level associated with the signal from sound waves. The purpose of this research is to know the accuracy result from Fast Fourier Transform and Bayes method in pattern recognition. The Fast Fourier Transform method is used for feature extraction and Bayes method is used to calculate the sound probability value between the train data and test data, then Bayes Method is used to determine the result of the introduction of some previously stored train data. This research was made using Matlab R2016a, by matching the pattern of human sound that has been made before or called train data with new sound pattern or called test data. Testing is done on voice in the database and the voice is not in the database. Test results for voice in the database were 96% for first men and 76% for first women. While testing for voice is not in the database is 46% for second men and 50% for second women

The Application of Fast Fourier Transform and Convolution Techniques to Picosecond Continuum Spectroscopy

1983 ◽  
Vol 37 (3) ◽  
pp. 273-279 ◽  
Author(s):  
K. L. Sala ◽  
R. W. Yip ◽  
R. LeSage
Keyword(s):  
Fourier Transform ◽  
Data Processing ◽  
Data Acquisition ◽  
Fast Fourier Transform ◽  
Experimental Technique ◽  
Transient Absorption ◽  
Computation Time ◽  
Spectroscopic Technique ◽  
Experimental Results ◽  
Data Acquisition And Processing

The use of the fast Fourier transform in the processing of photographic data obtained from picosecond continuum spectroscopy is described. The resulting reduction in the complexity and computation time has permitted all of the data acquisition and processing to be carried out with an eight-bit microcomputer. Specific examples of some key problems in the data processing that are peculiar to this spectroscopic technique and methods of overcoming these problems are discussed. Experimental results that serve to illustrate both the experimental technique itself as well as the versatility and reliability of the data processing algorithm are presented for the transient absorption of a Cr(III) complex in solutions.

Fast Fourier transform benchmark on X86 Xeon system for multimedia data processing

2015 ◽  
Vol 76 (4) ◽  
pp. 6015-6030 ◽  
Author(s):  
Young-Soo Park ◽  
Koo-Rack Park ◽  
Jin-Mook Kim ◽  
Hwa-Young Jeong
Keyword(s):  
Fourier Transform ◽  
Data Processing ◽  
Fast Fourier Transform ◽  
Multimedia Data

Design of the Power Parameter Measurement System Based on SOPC

2012 ◽  
Vol 503-504 ◽  
pp. 1338-1342
Author(s):  
Zhan Ying Tong ◽  
Jing Kui Mao
Keyword(s):  
Fourier Transform ◽  
Data Processing ◽  
Fast Fourier Transform ◽  
Measurement System ◽  
Parameter Measurement ◽  
Experimental Result ◽  
Time System ◽  
Power Parameter ◽  
Real Time System ◽  
Fpga Chip

In this paper the SOPC technology is applied to the power parameter measurement in a FPGA chip. The Fast Fourier Transform (FFT) algorithm implemented in the FPGA is the theory basis of the system, and the 32 bit NiosⅡ soft CPU nuclear is embedded in the FPGA, which can realize the functions of power signals samping, data processing, storage, display and so on. The experimental result shows that processing precision meets expectations, and achieving requirements of the real-time system, with advantages of high integration and flexible reconstruction.

scholarly journals Application of Hilbert Huang transform to identify the natural frequencies of steel frame

2019 ◽  
Vol 13 (2) ◽  
pp. 64-73 ◽  
Author(s):  
Nguyen Thanh Trung
Keyword(s):  
Fourier Transform ◽  
Data Processing ◽  
Fast Fourier Transform ◽  
Natural Frequency ◽  
Time Domain ◽  
Natural Frequencies ◽  
Processing Method ◽  
Steel Frame ◽  
Hilbert Huang Transform ◽  
Data Processing Method

Identification of dynamic structural characteristics such as natural frequency based on measured vibration responses at site is one of the important steps in the structural investigation work of loading test and structural health monitoring. During the service stage, the dynamic characteristics can be changed due to the stiffness reduction and nonlinear of structure under extrema excitation. Therefore, the identification of instantaneous parameters of structure is very necessary in detecting and monitoring the structural deterioration continuously by the time. This paper presents the data processing method using Hilbert Huang Transform (HHT) algorithm in determining a time-dependent frequencies of steel frame. The vibration experiment for steel frame was conducted in this study. The acceleration responses in time domain were recorded and analyzed by HTT to determine the fundamental natural frequencies of frame. The instantaneous frequencies in the time domain of steel frame are the main finding in this research. The traditional data processing method using a Fast Fourier Transform (FFT) was conducted and compared with the HHT method. Keywords: Hilbert Huang Transform (HHT); steel frame; Fast Fourier Transform (FFT); natural frequency.

scholarly journals Frequency analyses of human voice using fast Fourier transform

2019 ◽  
Vol 13 (27) ◽  
pp. 174-181
Author(s):  
Jinan F. Mahdi
Keyword(s):  
Fourier Transform ◽  
Quantitative Analysis ◽  
Fast Fourier Transform ◽  
Relative Proportion ◽  
Point Of View ◽  
Human Voice ◽  
Modes Of Vibration ◽  
The Subject ◽  
The Voice

Quantitative analysis of human voice has been subject of interest and the subject gained momentum when human voice was identified as a modality for human authentication and identification. The main organ responsible for production of sound is larynx and the structure of larynx along with its physical properties and modes of vibration determine the nature and quality of sound produced. There has been lot of work from the point of view of fundamental frequency of sound and its characteristics. With the introduction of additional applications of human voice interest grew in other characteristics of sound and possibility of extracting useful features from human voice. We conducted a study using Fast Fourier Transform (FFT) technique to analyze human voice to identify different frequencies present in the voice with their relative proportion while pronouncing selected words like numbers. Details of findings are presented

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