Kyoko watanabe (75 resultados)

hardcover. Condición: Like New. Like New. First Edition. Publisher: Simon & Schuster, New York, 2000. FINE hardcover book in FINE mylar-protected dust-jacket. First Edition, First Printing. Pristine. As new. Unread.

Hardcover. Condición: Very Good. Estado de la sobrecubierta: Poor. 355 pp. Solidly bound copy with minimal external wear, crisp pages and clean text. Small damage to both top of dj and front cover board near top of spine. Fullbrook/Massand (Jacket Design); Debra Lill (Jacket Photo); Ernst Kucklich (Case Photo); Marie-Reine Mattera (Author Photo); Kyoko Watanabe (Design); Granjon (Text Set) (ilustrador).…

Hardcover. Condición: Like New. Estado de la sobrecubierta: Like New. 308 pp. Flawless, fresh, sharp, tight copy with crisp pages and clean text. Flawless dj. Emily Mahon (Jacket Design); Roger Haile (Jacket & Author Photo); Kyoko Watanabe (Design) (ilustrador).

Hardcover. Condición: Very Good. Estado de la sobrecubierta: Very Good. Copyright © 2004 Barbara Delinsky. 355 pp. A great, almost spotlessly clean copy and dust jacket! Solidly and tightly bound, essentially and nearly flawless copy and dust jacket with minimal internal and external wear and use. Copy with crisp pages, clean text, and light shelf wear. Few minor stains on fore-edge. Smooth covers. Minimally or mildly shelf worn. Dust jacket shows minimal wear around edges. John Fulbrook III (Jacket Design); Sean Justice/Getty Images (Jacket Photo); Marie-Reine Mattera (Author Photo); Kyoko Watanabe (Design) (ilustrador). …

Hardcover. Condición: Like New. Hardcover. Near fine / near fine dust jacket. SIGNED by author with inscription to previous owner. For any additional information or pictures, please inquire.

Condición: Fine. Estado de la sobrecubierta: Fine. First/1st. Caldwell's second novel, that followed The Rule of Four, which he coauthored with Dustin Thomason in 2004. "The instant New York Times bestseller from the author of the international sensation The Rule of Four combines a lost gospel, a contentious relic, and a dying pope's final wish into a "deliciously labyrinthine" (Providence Journal) intellectual thriller that "kicks off at ninety mph and doesn't slow down" (Associated Press). A mysterious exhibit is under construction at the Vatican Museums. The curator is murdered at a clandestine meeting on the outskirts of Rome a week before it opens. That same night, a violent break-in rocks the home of Greek Catholic priest Father Alex Andreou. When the papal police fail to identify a suspect in either crime, Father Alex decides that to find the killer he must reconstruct the secret of what a little-known, true-to-life fifth gospel known as the Diatessaron reveals about the church's most controversial holy relic. But just as he begins to understand the truth about his friend's death and its consequences for the future of the Christian church, Father Alex discovers a ruthless stalker is hunting him-an enemy with a vested stake in the exhibit that he must outwit to survive." Source: Simon & Schuster. 8vo hardcover in printed pictorial boards. Kyoko Watanabe; Paul J. Pugliese (ilustrador).…

Hardcover. Condición: Like New. Collectible, signed by author, edition! Excellent condition. Interior is tight, bright and clean. Hard covers are tight and stiff. Complete with original paper dust cover. Minor scuffing on the paper dust cover from shelf wear. 100% Satisfaction Guaranteed. All items are carefully enclosed with bubble wrap. We ship promptly and worldwide via US Post and will email you a tracking number. Signed by.…

Hardcover. Condición: Fine. Estado de la sobrecubierta: Fine. 1st Edition. 1st., 1st printing ; 192 pages ; 22 cm ; SIGNED by author on title page ; ISBN 9780060193607, 0060193603 ; OCLC 41272958 ; LCCN 99015621 ; LOC No PS3554.A844 L54 1999 ; gold and black cloth in color pictorial dustjacket ; Sister cannot say exactly when or where she was when she first saw--heard--that look, and maybe it was sometime at night after she lay down to sloop, but she saw it. Then her eyes sprang wide and her lips parted and she repeated over and over like a sinner's prayer how she would not sorry away like Marnie.-- From Like a Sister ;It is 1956 and Sister is only thirteen years old, but she is a mother to her two younger twin brothers and her toddler sister. Her mother, Marnie, has had a string of boyfriends, and her latest is more interested in building up business at his new café than he is in raising three children that are not his own. Marnie is involved in the café as well--but Sister is not exactly sure how. All she knows is that Marnie isn't around very much. Things weren't always this way--at one time they were close, "just like sisters." Now it seems they are strangers, and Sister has noticed that the neighbors are giving each other looks--looks that say that whatever Marnie is up to at the café, it isn't respectable. Deciding that she will not follow in Marnie's footsteps, Sister begins to take charge of her life, as best she can, by minding her manners, and by befriending her kindly next-door neighbor, Willa, who seems to Sister to be a fine example of how a mother should be. But then Ray Williams, a respected and powerful man in town, begins to notice the blossoming Sister, and when he realizes that she has no adult supervision, he sets his sights on her. Willa steps in to intervene, and Sister thinks she may have found salvation, but in Like a Sister, all is never what it seems. ; A haunting coming-of-age tale, Like a Sister will linger in the minds of readers long after the last page has been turned. -- Source: Publisher ; Janice Daugharty is Artist-in-Residence at Abraham Baldwin Agricultural College, in Tifton, Georgia. She is the author of one story collection and five novels: Dark of the Moon, Necessary Lies, Pawpaw Patch, Earl in the Yellow Shirt, and Whistle. ; FINE/FINE. Signed by Author(s). Book. …

Condición: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.

Hardcover. Condición: As New. Like new, never been used.

Condición: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Condición: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.

Condición: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Condición: New. Brand New Original US Edition. Customer service! Satisfaction Guaranteed.

Condición: New. Brand New! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 6-10 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.…

Condición: New.

Condición: New.

Condición: As New. Unread book in perfect condition.

Hardcover. Condición: Gut. Ex-library with stamp and library-signature. GOOD condition, some traces of use. Ancien Exemplaire de bibliothèque avec signature et cachet. BON état, quelques traces d'usure. Ehem. Bibliotheksexemplar mit Signatur und Stempel. GUTER Zustand, ein paar Gebrauchsspuren. C 1162: (1999) 9780792356837 Sprache: Englisch Gewicht in Gramm: 500.…

Condición: New. The use of flexible sigmoid functions makes artificial neural networks more versatile. This volume determines learning algorithms for sigmoid functions in several different learning modes using flexible structures of neural networks with new derivation algorithms. It is aimed at electrical, electronic, and mechanical control and systems engineers. Series: Intelligent Systems, Control and Automation: Science and Engineering. Num Pages: 252 pages, biography. BIC Classification: GPFC; TJFM. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 234 x 156 x 15. Weight in Grams: 537. . 1999. Hardback. . . . .…

Condición: New.

Condición: Fine. Size: 30cm.

Condición: New. pp. 252.

Condición: As New. Unread book in perfect condition.

Condición: New. pp. 350.

Condición: New. pp. 256.

Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - There is no strict definition of the term 'High Magnetic Field'. It has been proposed to use this term for magnetic fields that are technically difficult to generate and therefore need special equipment or large resources. Static fields above 20 T are apparently high magnetic fields in this sense, but in the case of pulsed field 40 T is easy to obtain and any field lower than this approximate limit should not be considered as 'high'. When a static field is used for materials processing, even 10 T is considered as 'high' because the long-term use of a conventional superconducting magnet is difficult. Recently, there has been much technical progress in producing high mag netic fields, both pulsed and static; in large part this is due to the devel opment of new materials. Complicated poly-helix coils are now replaced by simple Bitter coils made with plates of CuAg alloy with high strength and high conductivity; these are used in both water-cooled and hybrid magnets (now up to 45 Tat NHMFL, the US National High Magnetic Field Labora tory at Tallahassee, Florida). By using CuAg wire, a nondestructive pulsed field record of 80 T has been achieved at Osaka University. For daily use in experiments, 70-75 T should soon become available. Major facilities for static high fields worldwide are planning to generate fields over 40 T by increasing the electric power. On the other hand, the use of static high magnetic fields is expanding.…

Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 Chapter 3 Flexible Neural Networks . . . . . . . . . . . . . . . . . . . . . . . . 61 3. 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 3. 2 Flexible Unipolar Sigmoid Functions . . . . . . . . . . . . . . . . . . . . . . . . . . 62 3. 3 Flexible Bipolar Sigmoid Functions . . . . . . . . . . . . . . . . . . . . . . . . . . . 64 3. 4 Learning Algorithms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 3. 4. 1 Generalized learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 3. 4. 2 Specialized learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 3. 5 Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72 3. 6 Combinations of Flexible Artificial Neural Network Topologies . . . . 79 3. 7 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82 Chapter 4 Self-Tuning PID Control 85 4. 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 4. 2 PID Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 4. 3 Flexible Neural Network as an Indirect Controller . . . . . . . . . . . . . . . 91 4. 4 Self-tunig PID Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 4. 5 Simulation Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94 4. 5. 1 The Tank model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94 4. 5. 2 Simulation study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96 4. 5. 3 Simulation results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99 4. 6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105 Chapter 5 Self-Tuning Computed Torque Control: Part I 107 5. 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107 5. 2 Manipulator Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108 5. 3 Computed Torque Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110 5. 4 Self-tunig Computed Torque Control . . . . . . . . . . . . . . . . . . . . . . . . . 111 5. 5 Simulation Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115 5. 5. 1 Simultaneous learning of connection weights and SF para- ters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116 5. 5. 2 Learning of the sigmoid function parameters . . . . . . . . . . . . . 123 Vll 5. 5. 3 Simultaneous learning of SF parameters and output gains 129 5. 6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135 Chapter 6 Self-Tuning Computed Torque Control: Part II 137 6. 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137 6. 2 Simplification of Flexible Neural Networks . . . . . . . . . . . . . . . . . . . . 138 6. 3 Simulation Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140 6. 3. 1 Simultaneous learning of connection weights and sigmoid function parameter. …

Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 Chapter 3 Flexible Neural Networks . . . . . . . . . . . . . . . . . . . . . . . . 61 3. 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 3. 2 Flexible Unipolar Sigmoid Functions . . . . . . . . . . . . . . . . . . . . . . . . . . 62 3. 3 Flexible Bipolar Sigmoid Functions . . . . . . . . . . . . . . . . . . . . . . . . . . . 64 3. 4 Learning Algorithms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 3. 4. 1 Generalized learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 3. 4. 2 Specialized learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 3. 5 Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72 3. 6 Combinations of Flexible Artificial Neural Network Topologies . . . . 79 3. 7 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82 Chapter 4 Self-Tuning PID Control 85 4. 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 4. 2 PID Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 4. 3 Flexible Neural Network as an Indirect Controller . . . . . . . . . . . . . . . 91 4. 4 Self-tunig PID Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 4. 5 Simulation Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94 4. 5. 1 The Tank model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94 4. 5. 2 Simulation study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96 4. 5. 3 Simulation results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99 4. 6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105 Chapter 5 Self-Tuning Computed Torque Control: Part I 107 5. 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107 5. 2 Manipulator Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108 5. 3 Computed Torque Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110 5. 4 Self-tunig Computed Torque Control . . . . . . . . . . . . . . . . . . . . . . . . . 111 5. 5 Simulation Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115 5. 5. 1 Simultaneous learning of connection weights and SF para- ters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116 5. 5. 2 Learning of the sigmoid function parameters . . . . . . . . . . . . . 123 Vll 5. 5. 3 Simultaneous learning of SF parameters and output gains 129 5. 6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135 Chapter 6 Self-Tuning Computed Torque Control: Part II 137 6. 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137 6. 2 Simplification of Flexible Neural Networks . . . . . . . . . . . . . . . . . . . . 138 6. 3 Simulation Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140 6. 3. 1 Simultaneous learning of connection weights and sigmoid function parameter. …

Condición: New.