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関連する概念動画

Discrete Fourier Transform01:15

Discrete Fourier Transform

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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...
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Discrete-time Fourier transform01:26

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The Discrete-Time Fourier Transform (DTFT) is an essential mathematical tool for analyzing discrete-time signals, converting them from the time domain to the frequency domain. This transformation allows for examining the frequency components of discrete signals, providing insights into their spectral characteristics. In the DTFT, the continuous integral used in the continuous-time Fourier transform is replaced by a summation to accommodate the discrete nature of the signal.
One of the notable...
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Basic Discrete Time Signals01:16

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The unit step sequence is defined as 1 for zero and positive values of the integer n. This sequence can be graphically displayed using a set of eight sample points, showing a step function starting from n=0 and remaining constant thereafter.
The unit impulse or sample sequence is mathematically expressed as zero for all n values except at n=0, where it is one. The unit impulse sequence, denoted by δ(n), is the first difference of the unit step sequence, while the unit step sequence u(n) is the...
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Discrete-Time Fourier Series01:20

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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.
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In any LTI (Linear Time-Invariant) system, the convolution of two signals is denoted using a convolution operator, assuming all initial conditions are zero. The convolution integral can be divided into two parts: the zero-input or natural response and the zero-state or forced response, with t0 indicating the initial time.
To simplify the convolution integral, it is assumed that both the input signal and impulse response are zero for negative time values. The graphical convolution process...
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BIBO stability of continuous and discrete -time systems01:24

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System stability is a fundamental concept in signal processing, often assessed using convolution. For a system to be considered bounded-input bounded-output (BIBO) stable, any bounded input signal must produce a bounded output signal. A bounded input signal is one where the modulus does not exceed a certain constant at any point in time.
To determine the BIBO stability, the convolution integral is utilized when a bounded continuous-time input is applied to a Linear Time-Invariant (LTI) system....
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Updated: Jan 29, 2026

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新しい最大カオス離散マップについて

Hyojeong Choi1, Gangsan Kim1, Hong-Yeop Song1

  • 1Department of Electrical and Electronic Engineering, Yonsei University, Seoul 03722, Republic of Korea.

Entropy (Basel, Switzerland)
|January 28, 2026
PubMed
まとめ

この研究は、新しい離散カオスマップが最適なカオス発散を示すことを証明しています。このマップは、同じ出力を生成する入力が同じパリティを持つことを保証し、暗号アプリケーションを強化します。

キーワード:
カオス写像離散リャプノフ指数離散カオス有限精度乱数列スキューテント写像

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科学分野:

  • 数論
  • 離散数学
  • 暗号理論

背景:

  • 離散スキューテント写像はカオス理論の基礎です。
  • カオスマップにおける入力と出力の関係を理解することは、その応用にとって重要です。
  • カオスマップのパリティ特性は、その根底にある構造を明らかにすることができます。

研究 の 目的:

  • 証明された双射特性を持つ新しい離散カオスマップを導入すること。
  • 提案されたマップが順列マップの中で最大カオス発散を達成することを示すこと。
  • 数値実験を通じて新しいマップのカオス的挙動を分析すること。

主な方法:

  • 対称離散スキューテント写像のパリティ特性の証明(定理1)。
  • 新しい離散カオスマップの双射性の定義と証明(定義1、定理2)。
  • カオス特性を評価するための離散リャプノフ指数(dLE)の計算と分析(定理3)。
  • 近似エントロピー、順列エントロピー、NIST SP800-22テスト、相関分析を含む数値実験の実施。

主要な成果:

  • 対称離散スキューテント写像において、同じ出力を生成する入力は同じパリティを共有することを確立しました。
  • すべてのパラメータに対して双射であることが証明された新しい離散カオスマップを開発しました。
  • 提案されたマップのdLEが順列マップで可能な最大値に近づくことを示し、高いカオス発散を示しました。
  • 数値実験により、エントロピー計算と統計的検定を通じてマップのカオス的挙動を確認しました。

結論:

  • 提案された離散カオスマップは、双射性や最大カオス発散などの望ましい特性を持っています。
  • パリティ特性は、潜在的な暗号アプリケーションにユニークな特徴を提供します。
  • このマップは、疑似乱数生成および安全な通信システムのための強力な候補となります。