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Upsampling01:22

Upsampling

309
Managing signal sampling rates is essential in digital signal processing to maintain signal integrity. A decimated signal, characterized by a reduced frequency range due to its lower sampling rate, can be upsampled by inserting zeros between each sample. This upsampling process expands the original spectrum and introduces repeated spectral replicas at intervals dictated by the new Nyquist frequency. To refine this zero-inserted sequence, it is passed through a lowpass filter with a cutoff...
309
Downsampling01:20

Downsampling

250
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...
250
Sampling Plans01:23

Sampling Plans

257
Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
257
Fixed Action Patterns01:06

Fixed Action Patterns

16.4K
A fixed action pattern (FAP) is a specific, hard-wired sequence of behaviors that occurs in response to an external stimulus, called a sign stimulus. The behavior is “fixed” because it is essentially unchangeable—proceeding similarly across individuals of a species every time it occurs.
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Bandpass Sampling01:17

Bandpass Sampling

258
In signal processing, bandpass sampling is an effective technique for sampling signals that have most of their energy concentrated within a narrow frequency band. This type of signal is known as a bandpass signal. The key principle of bandpass sampling involves sampling the signal at a rate that is greater than twice the signal's bandwidth to prevent aliasing.
A bandpass signal has a spectrum with a lower frequency limit, denoted as ω1, and an upper frequency limit, denoted as ω2....
258
Aliasing01:18

Aliasing

224
Accurate signal sampling and reconstruction are crucial in various signal-processing applications. A time-domain signal's spectrum can be revealed using its Fourier transform. When this signal is sampled at a specific frequency, it results in multiple scaled replicas of the original spectrum in the frequency domain. The spacing of these replicas is determined by the sampling frequency.
If the sampling frequency is below the Nyquist rate, these replicas overlap, preventing the original...
224

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Updated: Sep 8, 2025

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
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Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

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アクションサブサンプリングは,大規模なアクションスペースでの政策圧縮をサポートします.

Shuze Liu1, Samuel Joseph Gershman2,3

  • 1PhD Program in Neuroscience, Harvard University, Cambridge, Massachusetts, United States of America.

PLoS computational biology
|September 5, 2025
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まとめ

認知の限界は,行動の検討セットと政策の複雑さを制限することで意思決定に影響します. この研究は,人間が資源の制限の下で近似最適の選択を行うためにこれらの戦略をどのように適応させるかを示す統一された枠組みを紹介しています.

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科学分野:

  • 認知科学
  • 計算神経科学
  • 行動経済学

背景:

  • 現実世界での決断には 広大な行動空間と 認知の限界が含まれます
  • 以前の研究では,行動検討セットと政策の複雑さを別々に調査した.
  • これらの認知的制約の相互作用はよく理解されていません.

研究 の 目的:

  • 行動検討セットと政策の複雑さを統合した政策圧縮のための統一された資源合理的枠組みを提示する.
  • 行動考慮の減少と政策の複雑さとの相互作用からサブ最適性を特徴付ける.
  • オプション生成における経験的観測を説明し,実験で予測を検証する.

主な方法:

  • 政策圧縮のための資源合理的な枠組みを開発しました.
  • サブオプティマリティと戦略の相互作用を分析するシミュレーションを実施した.
  • 文脈的な複数武装の強盗実験を設計し実行した.

主要な成果:

  • シミュレーションにより,政策の複雑さと行動の考慮のセットサイズとの間の複雑な相互作用が示されました.
  • 偏好的なサンプリングや負荷下での反応の相関性の増加などの経験的現象が説明されました.
  • 人間参加者は,行動の検討セットと政策の複雑さを,タスクに依存した方法で柔軟に適応しました.

結論:

  • 認知資源の制約は意思決定戦略を大きく左右する.
  • 人間は最適に近い状態を維持するために 適応的なメタコグニティブ戦略を採用します
  • 認知の限界下での意思決定を理解するには 統一された枠組みが不可欠です