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Related Concept Videos

Types of Errors: Detection and Minimization01:12

Types of Errors: Detection and Minimization

Error is the deviation of the obtained result from the true, expected value or the estimated central value. Errors are expressed in absolute or relative terms.
Absolute error in a measurement is the numerical difference from the true or central value. Relative error is the ratio between absolute error and the true or central value, expressed as a percentage.
Errors can be classified by source, magnitude, and sign. There are three types of errors: systematic, random, and gross.
Systematic or...
Encoding01:19

Encoding

Information enters the brain through encoding, which is the input of information into the memory system. Once sensory information is received from the environment, the brain labels or codes it. The information is then organized with similar information and connected to existing concepts. Encoding occurs through automatic processing and effortful processing.
Automatic processing involves the encoding of details like time, space, frequency, and the meaning of words, usually done without conscious...
PI Controller: Design01:24

PI Controller: Design

Proportional Integral (PI) controllers are a fundamental component in modern control systems, widely used to enhance performance and mitigate steady-state errors. They are particularly effective in applications such as automatic brightness adjustment on smartphones, where they excel at mitigating steady-state errors for step-function inputs. Unlike PD controllers, which require time-varying errors to function optimally, PI controllers leverage their integral component to address residual...
Distance Corrections01:15

Distance Corrections

To achieve precise distance measurements, especially in surveying and construction, certain corrections must be applied to account for potential sources of error like the standardization errors, temperature variations, and slope adjustments.Standardization error emerges when measurement equipment undergoes changes, such as wear, repairs, or weather impacts. To address this, surveyors compare the equipment’s readings to a standard. This process identifies any deviation that might lead to...
Design Example01:23

Design Example

The innovation of touch-tone telephony revolutionized the telecommunications industry by replacing the traditional rotary dial with a dual-tone multi-frequency (DTMF) signaling system. This system uses a matrix-style keypad with buttons arranged in four rows and three columns, creating 12 distinct signals each assigned to a pair of frequencies. Each button press results in a simultaneous generation of two sinusoidal tones – one from a low-frequency group (697 to 941 Hz) and one from a...
PD Controller: Design01:26

PD Controller: Design

In automotive engineering, car suspension systems often employ Proportional Derivative (PD) controllers to enhance performance. PD controllers are utilized to adjust the damping force in response to road conditions. A controller, acting as an amplifier with a constant gain, demonstrates proportional control, with output directly mirroring input.
Designing a continuous-data controller requires selecting and linking components like adders and integrators, which are fundamental in Proportional,...

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Updated: Jun 7, 2026

Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping
09:43

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Published on: March 20, 2017

Optical error-correction coding encoder and decoder: design considerations.

W Kawakami, K I Kitayama

    Applied Optics
    |November 6, 2010
    PubMed
    Summary

    Novel all-optical systems for error detection and correction using linear codes are presented. These systems achieve high throughput for image processing, utilizing optical vector-matrix multipliers and lookup tables.

    Area of Science:

    • Optoelectronics
    • Information Theory
    • Computer Engineering

    Background:

    • Error detection and correction are crucial for reliable data transmission and storage.
    • Linear codes, such as Hamming codes, are widely used for error management.
    • All-optical computing offers potential for high-speed data processing.

    Purpose of the Study:

    • To propose novel all-optical parallel implementations of encoder and decoder systems for linear codes.
    • To evaluate the system throughput and hardware requirements for practical applications.
    • To demonstrate the feasibility of optical error detection and correction for image data.

    Main Methods:

    • Development of all-optical encoder and decoder architectures.
    • Integration of optical vector-matrix multipliers and optical lookup tables.

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  • System performance evaluation using a (7, 4) Hamming code for a 1000 × 1000 pixel image.

    • Main Results:

    • Achieved a best throughput of approximately 5.6 × 10^10 pixels/s.
    • Projected hardware size of 1 cm × 1 cm using near-future ferroelectric liquid-crystal devices.
    • Demonstrated a combination of time- and space-division techniques for enhanced performance.

    Conclusions:

    • All-optical parallel systems offer a viable solution for high-speed error detection and correction.
    • The proposed architectures are efficient in terms of throughput and hardware footprint.
    • This technology holds promise for advanced optical information processing applications.