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Propagation of Uncertainty from Random Error00:59

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An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...
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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...
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Signal processing techniques are essential for accurately converting continuous signals to digital formats and vice versa. When a continuous signal is sampled with a period T, the resulting sampled signal exhibits replicas of the original spectrum in the frequency domain, spaced at intervals equal to the sampling frequency. To handle this sampled signal, a zero-order hold method can be applied, which creates a piecewise constant signal by retaining each sample's value until the next...
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Lossy Lines and Overvoltages01:22

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Transmission-line series resistance and shunt conductance cause three primary effects: attenuation, distortion, and power losses.
Attenuation
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Reducing Line Loss01:18

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In a three-phase circuit, line loss is an indicator of energy dissipated as heat due to the resistance of transmission lines. To address this, incorporating transformers into the system—a step-up transformer at the source and a step-down transformer at the load—is a strategic solution. Two three-phase transformers are introduced to improve this.
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Propagation of Uncertainty from Systematic Error01:10

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The atomic mass of an element varies due to the relative ratio of its isotopes. A sample's relative proportion of oxygen isotopes influences its average atomic mass. For instance, if we were to measure the atomic mass of oxygen from a sample, the mass would be a weighted average of the isotopic masses of oxygen in that sample. Since a single sample is not likely to perfectly reflect the true atomic mass of oxygen for all the molecules of oxygen on Earth, the mass we obtain from this...
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Related Experiment Video

Updated: Mar 24, 2026

Recording Ultra-Realistic Full-Color Analog Holograms for Use in a Moving Hologram Display
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Concurrent Codes: A Holographic-Type Encoding Robust against Noise and Loss.

David M Benton1

  • 1Aston Institute of Photonic Technologies, Aston University, Aston Triangle, Birmingham, United Kingdom.

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Concurrent coding offers robust data transmission, correcting random and burst errors even with substantial signal loss. This efficient encoding scheme outperforms cyclic codes in power requirements and data recovery.

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Area of Science:

  • Information Theory
  • Error Correction Coding
  • Digital Communications

Background:

  • Traditional error correction codes struggle with simultaneous random and burst errors.
  • Signal loss and noise significantly degrade data integrity in digital transmissions.
  • Cyclic codes are widely used but have limitations in efficiency and error correction capabilities.

Purpose of the Study:

  • To introduce and evaluate a novel concurrent coding scheme.
  • To demonstrate the robustness of concurrent coding against noise and signal loss.
  • To compare the efficiency and performance of concurrent coding with existing methods like cyclic codes.

Main Methods:

  • Development of a concurrent coding scheme with 'holographic' properties.
  • Testing the scheme's performance under various noise levels (down to -18dB SNR).
  • Evaluating reconstruction capabilities with significant data loss (up to 40% contiguous missing data).

Main Results:

  • Concurrent coding achieves perfect decoding at -18dB signal-to-noise ratio.
  • The scheme enables perfect reconstruction with up to 40% of data missing.
  • Demonstrates 50% greater efficiency in transmitted power compared to cyclic codes.

Conclusions:

  • Concurrent coding provides a highly robust and efficient solution for error correction.
  • The scheme effectively handles simultaneous random and burst errors without relying on cyclic codes.
  • A predictive model for decoding complexity and error thresholds has been established.