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Related Concept Videos

Properties of Fourier Transform I01:21

Properties of Fourier Transform I

The application of Fourier Transform properties in radio broadcasting is multifaceted, enabling significant advancements in the way signals are transmitted and received. Key areas where these properties are utilized include simultaneous multi-channel transmission, audio clip speed adjustments, live broadcast delays for different time zones, audio frequency adjustments, and signal demodulation.
In radio broadcasting, multiple audio signals often need to be transmitted simultaneously. The Fourier...
Fast Fourier Transform01:10

Fast Fourier Transform

The Fast Fourier Transform (FFT) is a computational algorithm designed to compute the Discrete Fourier Transform (DFT) efficiently. By breaking down the calculations into smaller, manageable sections, the FFT significantly reduces the computational complexity involved. Direct computation of an N-point DFT requires N2 complex multiplications, whereas the FFT algorithm needs only (N/2)log⁡2N multiplications, offering a much faster performance.
The computational efficiency of the FFT becomes...
Discrete Fourier Transform01:15

Discrete Fourier Transform

The Discrete Fourier Transform (DFT) is a fundamental tool in signal processing, extending the discrete-time Fourier transform by evaluating discrete signals at uniformly spaced frequency intervals. This transformation converts a finite sequence of time-domain samples into frequency components, each representing complex sinusoids ordered by frequency. The DFT translates these sequences into the frequency domain, effectively indicating the magnitude and phase of each frequency component present...
Discrete-Time Fourier Series01:20

Discrete-Time Fourier Series

The Discrete-Time Fourier Series (DTFS) is a fundamental concept in signal processing, serving as the discrete-time counterpart to the continuous-time Fourier series. It allows for the representation and analysis of discrete-time periodic signals in terms of their frequency components. Unlike its continuous counterpart, which utilizes integrals, the calculation of DTFS expansion coefficients involves summations due to the discrete nature of the signal.
For a discrete-time periodic signal x[n]...
The Cochlea01:13

The Cochlea

The cochlea is a coiled structure in the inner ear that contains hair cells—the sensory receptors of the auditory system. Sound waves are transmitted to the cochlea by small bones attached to the eardrum called the ossicles, which vibrate the oval window that leads to the inner ear. This causes fluid in the chambers of the cochlea to move, vibrating the basilar membrane.
Perception of Sound Waves01:01

Perception of Sound Waves

The human ear is not equally sensitive to all frequencies in the audible range. It may perceive sound waves with the same pressure but different frequencies as having different loudness. Moreover, the perception of sound waves depends on the health of an individual's ears, which decays with age. The health of one's ears may also be affected by regular exposure to loud noises.
The pitch of a sound depends on the frequency and the pressure amplitude of the source. Two sounds of the same frequency...

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Wideband Optical Detector of Ultrasound for Medical Imaging Applications
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Published on: May 11, 2014

Fiber-optic acoustic Fourier transducer for audio sound processing.

G Zhou, L Bintz, D Z Anderson

    Applied Optics
    |August 20, 2010
    PubMed
    Summary

    This study introduces a novel fiber-optic acoustic transducer. This device uses optical fibers and a novelty filter to detect sound waves, enabling acoustic signal analysis.

    Area of Science:

    • Photonics
    • Acoustics
    • Optical Engineering

    Background:

    • Traditional acoustic transducers face limitations in sensitivity and frequency response.
    • Developing new methods for acoustic signal detection is crucial for various applications.

    Purpose of the Study:

    • To demonstrate a novel fiber-optic acoustic transducer.
    • To analyze its performance in the audio-frequency regime.
    • To explore holographic storage of acoustic patterns.

    Main Methods:

    • Utilizing an array of 120 multimode optical fibers as cantilevered mechanical resonators.
    • Employing a photorefractive novelty filter to extract acoustic information from reflected laser light.
    • Implementing holographic storage using a LiNbO(3) crystal.

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    Main Results:

    • The fiber-optic acoustic transducer operates effectively in the audio-frequency range (100 Hz to 5 kHz).
    • The device's output provides a Fourier transform of the acoustic signal.
    • Background intensity indicates a driving amplitude of approximately 50 A.

    Conclusions:

    • The developed fiber-optic acoustic transducer offers a new approach for acoustic sensing.
    • The system demonstrates potential for high-fidelity acoustic signal processing and storage.
    • This technology opens avenues for advanced optical-acoustic hybrid systems.