Jove
Visualize
お問い合わせ

関連する概念動画

Downsampling01:20

Downsampling

251
When considering a sampled sequence with zero values between sampling instants, one can replace it by taking every N-th value of the sequence. At these integer multiples of N, the original and sampled sequences coincide. This process, known as decimation, involves extracting every N-th sample from a sequence, thereby creating a more efficient sequence.
The Fourier transform of the decimated sequence reveals a combination of scaled and shifted versions of the original spectrum. This...
251
Boundary Conditions: Lossless Lines01:21

Boundary Conditions: Lossless Lines

152
Consider a single-phase, two-wire, lossless transmission line terminated by an impedance at the receiving end and a source with Thevenin voltage and impedance at the sending end. The line, with length, has a surge impedance and wave velocity determined by the line's inductance and capacitance.
At the receiving end, the boundary condition states that the voltage equals the product of the receiving-end impedance and current. This relationship is expressed as a function of the incident and...
152
Per-Unit Sequence Models01:26

Per-Unit Sequence Models

116
An ideal Y-Y transformer, grounded through neutral impedances, displays per-unit sequence networks akin to those of a single-phase ideal transformer when subjected to balanced positive- or negative-sequence currents. These currents do not produce neutral currents, and their associated voltage drops.
Zero-sequence currents, which are identical in magnitude and phase, generate a neutral current, resulting in voltage drops across the neutral impedance and the low-voltage winding. If the...
116
Lossless Lines01:23

Lossless Lines

169
In electrical engineering, a lossless transmission line is characterized by a purely imaginary propagation constant and a resistive characteristic impedance. The ABCD parameters, which describe the relationship between the input and output voltages and currents, indicate an equivalent π circuit with an imaginary series impedance and a shunt admittance. This results in a transmission line that, when the product of the phase constant (beta) and the length of the line is less than pi,...
169
Reducing Line Loss01:18

Reducing Line Loss

193
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.
With a step-up transformer at the source, the voltage is increased, thereby reducing the current in the transmission lines since power loss...
193
Wald-Wolfowitz Runs Test I01:17

Wald-Wolfowitz Runs Test I

740
The Wald-Wolfowitz test, also known as the runs test, is a nonparametric statistical test used to assess the randomness of a sequence of two different types of elements (e.g., positive/negative values, successes/failures). It examines whether the order of the elements in a sequence is random or if there is a pattern or trend present. This nonparametric test applies to any ordered data despite the population and sample data distribution, even if a higher sample size is available.
The test works...
740

こちらも読む

関連記事

共著者、ジャーナル、引用グラフによってこの研究に関連する記事。

並び替え
Same author

Commentary to "The human intelligence evolved from proximal <i>cis</i>-regulatory saltations".

Quantitative biology (Beijing, China)·2026
Same author

The human intelligence evolved from proximal <i>cis</i>-regulatory saltations.

Quantitative biology (Beijing, China)·2026
Same author

A four eigen-phase model of multi-omics unveils new insights into yeast metabolic cycle.

NAR genomics and bioinformatics·2025
Same author

Temporospatial hierarchy and allele-specific expression of zygotic genome activation revealed by distant interspecific urochordate hybrids.

Nature communications·2024
Same author

A data integration approach unveils a transcriptional signature of type 2 diabetes progression in rat and human islets.

PloS one·2023
Same author

RegScaf: a regression approach to scaffolding.

Bioinformatics (Oxford, England)·2022
JoVE
x logofacebook logolinkedin logoyoutube logo
JoVEについて
概要リーダーシップブログJoVEヘルプセンター
著者向け
出版プロセス編集委員会範囲と方針査読よくある質問投稿
図書館員向け
推薦の声購読アクセスリソース図書館諮問委員会よくある質問
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experimentsアーカイブ
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教員リソースセンター教員サイト
利用規約
プライバシーポリシー
ポリシー

関連する実験動画

Updated: Sep 10, 2025

Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples
07:30

Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples

Published on: June 8, 2020

12.2K

データシーケンスに関する経験的無損失圧縮

Lei M Li1,2

  • 1State Key Laboratory of Mathematical Science, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China.

Entropy (Basel, Switzerland)
|August 28, 2025
PubMed
まとめ

この研究では,最適の最小限圧縮のために,標準化された最大確率分布 (NML) を導入して,無損失のデータ圧縮境界を探索します. この研究は,離散データと連続データの両方に適用できる正確なNMLコード長方程式を導き出し,DNA配列圧縮でそれを検証します. この研究は,データ圧縮の限界と生物情報学の実用的な応用に関する理解を深める.

キーワード:
ベイジアンDNAについてエントロピー局所的な非対称的正規性損失のない圧縮標準化された最大確率予測する

さらに関連する動画

Quasi-light Storage for Optical Data Packets
07:45

Quasi-light Storage for Optical Data Packets

Published on: February 6, 2014

11.0K
Lensless Fluorescent Microscopy on a Chip
11:23

Lensless Fluorescent Microscopy on a Chip

Published on: August 17, 2011

17.8K

関連する実験動画

Last Updated: Sep 10, 2025

Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples
07:30

Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples

Published on: June 8, 2020

12.2K
Quasi-light Storage for Optical Data Packets
07:45

Quasi-light Storage for Optical Data Packets

Published on: February 6, 2014

11.0K
Lensless Fluorescent Microscopy on a Chip
11:23

Lensless Fluorescent Microscopy on a Chip

Published on: August 17, 2011

17.8K

科学分野:

  • 情報理論
  • データ圧縮
  • 統計的推論

背景:

  • コルモゴロフの複雑性は,無損失のデータ圧縮のための計算不可能な理論的境界を提供します.
  • シャノンのソースコーディング定理は,平均圧縮をnHとして定義し,nはシーケンス長,Hはエントロピーである.
  • 最大確率推定 (MLE) は,しばしば真の圧縮枠を過小評価する.

研究 の 目的:

  • 個々のデータシーケンスの無損失圧縮を導出し分析する.
  • データの圧縮のための標準化された最大確率分布 (NML) の最適性を調査する.
  • 圧縮された計算を離散データと連続データの両方に拡張し,バイオインフォマティクスに応用する.

主な方法:

  • ミニマックス意味での最適であることが示されているNML分布を使用します.
  • NMLのアシンプトティックコードの長さを得るために,局所アシンプトティック正規性を適用する.
  • 最適なコードの長さを予測するベイジアンアプローチを開発し,混合コードに導きます.
  • 異なる解析モデルを使用して,タンパク質をコードするDNA配列の圧縮限界を計算する.

主要な成果:

  • NMLのコードの長さは,分析的にnH (θ^n) + (d/2) log (n/2π) + log (∫) となる.
  • ベイジアン予測で得られた混合コードの長さは,nH (θ^n) + (d/2) log (n/2π) + log (n) です.
  • DNA配列の圧縮は,解析がアミノ酸コドンと整合すると最大化され,実用的な応用が示されます.
  • 経験的な圧縮境界は,辞書サイズが大きくなると改善されます.

結論:

  • NML分布は,データ圧縮限界に最適な計算可能なアプローチを提供します.
  • 派生したアシンプトティック式は,離散的および連続的なデータ圧縮の両方に正確な推定を提供します.
  • 解析戦略は,特に生物学的配列の圧縮効率に大きな影響を与える.
  • この研究は,さまざまなデータ型における理論的な圧縮限界を理解し,計算するための堅固な枠組みを提供します.