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Record Nr. |
UNINA9910149152503321 |
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Titolo |
回路理論 / / 渡部英二著 |
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Pubbl/distr/stampa |
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東京, : オーム社, 2012.10 |
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東京 : , : オーム社, , 2012 |
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ISBN |
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Descrizione fisica |
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1 online resource (160 pages) |
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Collana |
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Classificazione |
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Altri autori (Persone) |
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Soggetti |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Nota di contenuto |
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表紙 -- 発行にあたって -- はしがき -- 目次 -- １章 回路と回路素子 -- 1 回路と信号処理 -- 2 電源と回路素子 -- 3 回路とシステム -- 4 回路の基本的性質 -- 5 過渡状態と定常状態 -- ●練習問題 -- ２章 線形微分方程式と回路の応答 -- 1 RCおよびRL回路の時間応答 -- 2 RLC回路の時間応答 -- ●練習問題 -- ３章 ラプラス変換と回路の応答 -- 1 ヘビサイドの演算子法 -- 2 ラプラス変換の導入 -- 3 ラプラス変換の性質 -- 4 単位インパルス信号 -- 5 繰返し信号のラプラス変換 -- 6 微分方程式とラプラス変換 -- 7 回路関数とインパルス応答 -- 8 ラプラス逆変換 -- 9 ラプラス変換を用いる過渡解析 -- ●練習問題 -- ４章 回路関数 -- 1 駆動点関数と伝達関数 -- 2 正弦波定常応答と周波数特性 -- 3 簡単な回路の回路関数 -- 4 2ポート回路の動作量 -- 5 回路の安定性 -- 6 正実関数 -- 7 リアクタンス2ポート回路の電力伝送 -- ●練習問題 -- ５章 フーリエ変換と回路の応答 -- 1 フーリエ変換 -- 2 フーリエ級数 -- 3 デルタ関数とフーリエ変換 -- 4 線形回路の応答 -- ●練習問題 -- 付録 -- 1 2ポートパラメータ -- 練習問題解答･解説 -- 参考文献 -- 索引 -- 奥付. |
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2. |
Record Nr. |
UNINA9910969239003321 |
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Titolo |
Bayesian phylogenetics : methods, algorithms, and applications / / edited by Ming-Hui Chen, Lynn Kuo, and Paul O. Lewis, University of Connecticut Storrs, USA |
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Pubbl/distr/stampa |
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Boca Raton : , : CRC Press, , [2014] |
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©2014 |
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ISBN |
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1-04-021919-5 |
0-429-18426-3 |
1-4665-0079-4 |
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Edizione |
[1st ed.] |
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Descrizione fisica |
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1 online resource (391 p.) |
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Collana |
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Chapman and Hall/CRC Mathematical and Computational Biology Series |
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Disciplina |
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Soggetti |
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Phylogeny |
Biometry |
Molecular genetics |
Bayesian statistical decision theory |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references. |
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Nota di contenuto |
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Front Cover; Contents; List of Figures; List of Tables; Preface; Editors; Contributors; Chapter 1: Bayesian phylogenetics: methods, computational algorithms, and applications; Chapter 2: Priors in Bayesian phylogenetics; Chapter 3: Inated density ratio (IDR) method for estimating marginal likelihoods in Bayesian phylogenetics; Chapter 4: Bayesian model selection in phylogenetics and genealogy-based population genetics; Chapter 5: Variable tree topology stepping-stone marginal likelihood estimation; Chapter 6: Consistency of marginal likelihood estimation when topology varies |
Chapter 7: Bayesian phylogeny analysisChapter 8: SMC (sequential Monte Carlo) for Bayesian phylogenetics; Chapter 9: Population model comparison using multi-locus datasets; Chapter 10: Bayesian methods in the presence of recombination; Chapter 11: Bayesian nonparametric phylodynamics; Chapter 12: Sampling and summary statistics of endpoint-conditioned paths in DNA sequence evolution; Chapter 13: Bayesian inference of species divergence times; Bibliography; Back |
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Sommario/riassunto |
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Offering a rich diversity of models, Bayesian phylogenetics allows evolutionary biologists, systematists, ecologists, and epidemiologists to obtain answers to very detailed phylogenetic questions. Suitable for graduate-level researchers in statistics and biology, Bayesian Phylogenetics: Methods, Algorithms, and Applications presents a snapshot of current trends in Bayesian phylogenetic research. Encouraging interdisciplinary research, this book introduces state-of-the-art phylogenetics to the Bayesian statistical community and, likewise, presents state-of-the- |
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