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Related Concept Videos

Reconstruction of Signal using Interpolation01:10

Reconstruction of Signal using Interpolation

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 sampling...
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Spin systems where the difference in chemical shifts of the coupled nuclei is greater than ten times J are called first-order spin systems. These nuclei are weakly coupled, and their chemical shifts and coupling constant can generally be estimated from the well-separated signals in the spectrum.
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Aliasing

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Classification of Signals

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Related Experiment Video

Updated: May 29, 2026

Memorization-Based Training and Testing Paradigm for Robust Vocal Identity Recognition in Expressive Speech Using Event-Related Potentials Analysis
05:48

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Recognition of distorted patterns using the viterbi algorithm.

H Tanaka1, Y Hirakawa, S Kaneku

  • 1MEMBER, IEEE, Department of Electrical Engineering, Kobe University, Kobe, Japan.

IEEE Transactions on Pattern Analysis and Machine Intelligence
|August 27, 2011
PubMed
Summary

A novel pattern recognition system uses the Viterbi algorithm and a modified trellis for efficient and accurate classification of distorted patterns, mimicking human decision-making for improved performance.

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Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Pattern Recognition

Background:

  • Distorted pattern recognition remains a challenge in various fields.
  • Existing methods may lack efficiency or accuracy in handling complex distortions.

Purpose of the Study:

  • To introduce a new recognition system for distorted patterns.
  • To enhance decision accuracy and processing efficiency.

Main Methods:

  • Utilized the Viterbi algorithm.
  • Developed a modified trellis incorporating pattern statistics.
  • Designed the trellis to eliminate irrelevant pattern classes early.

Main Results:

  • Achieved successful recognition of handwritten English letters.
  • Demonstrated success in recognizing Japanese Katakana characters.
  • The system showed high accuracy and processing economy.

Conclusions:

  • The proposed system offers a universal approach for distorted pattern recognition.
  • The method effectively mimics human decision processes for improved outcomes.
  • This technique significantly reduces processing time while maintaining high accuracy.