Turn It On Again: Peter Gabriel, Phil Collins, and Genesis

Book Description

One of the most successful rock acts of all time, Genesis enjoyed a longevity exceeded only by the likes of the Rolling Stones and the Kinks, and provided a launching pad for superstars Peter Gabriel and Phil Collins. Turn It On Again is the first book to document the complete history of this popular and influential band, bringing their story up-to-date while placing them in the context of their time. It explores the relationship between the band and the remarkable solo careers it spawned. Drawing on dozens of exclusive interviews with band members past and present, as well as the musicians' friends and associates, author Dave Thompson chronicles Genesis' evolution from progressive-rock visionaries to mainstream rock stars, and the continuing careers of its most famous alumni.

Customer Reviews:

Gabriel rules (but even Collins sounds okay).......2005-04-18

I didn't expect to get past the Peter Gabriel years when I started reading this... who cares about Genesis after that, after all? But Thompson's writing style is so engaging, his humor is so strong and his passion so contagious that the band had broken up before I put the book down, and I was actually calling up my sister to borrow her copy of Abacab. Recmmended to everyone who actually cares about the music (and doesn't just want the dirt on their private lives...)

Reads Like a Discography.......2005-03-08

I've been fascinated with Peter Gabriel since I was 12 years old. I bought this book hoping to get some insight into the man and some info on those early Genesis albums. The book got off to a great start; discussing the early days of Genesis as school chums. But as the book progresses it begins to read like a discography. So-and-so made a solo album with these musicians, Genesis made this album, here's how it did in the market. The writing is marked by british style humor and language. But this does nothing to make this book any more interesting. It lacks insight into the bands characters and barely discusses what's going on in their lives. For example, at one point the book mentions Peter Gabriels wife Jill. Uh, no one told me he got married! who's this jill person? what does she do? Later the same thing happened with phil collins. When did he get a wife? early on there are some good stories but later all we hear about is that they put out a new album, who was on it and how the album did. a little about the sound too. oh well, they'll stay mythic in my mind.

Average customer rating:

Well thought-out, honest, comprehensive and sometimes even inspiring

'Dematerialize' by avoiding this book!

one of the top 10 books I've ever read, and I read a lot

Thoughtful advise

Oversimplified and Superficial

Dematerializing: Taming the Power of Possessions
Jane Hammerslough
Manufacturer: Perseus Publishing
ProductGroup: Book
Binding: Hardcover

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Similar Items:

The High Price of Materialism

The Overspent American: Why We Want What We Don't Need

The Paradox of Choice: Why More Is Less

Your Money or Your Life: Transforming Your Relationship with Money and Achieving Financial Independence

Psychology and Consumer Culture: The Struggle for a Good Life in a Materialistic World

ASIN: 0738203866
Release Date: 2001-09-18

Book Description

An insightful look at the misplaced faith we place in things, and meaningful advice on achieving material and emotional well-being.

Can the perfect new couch in your family room make for great times with your family? Does a diamond that costs two months' salary mean that love will last forever? In this era of high expectations and "low monthly payments," getting what you want has never seemed easier. And "getting what you want," in this environment, is increasingly linked to buying something. But is it always enough?

Picking up where "simplifying" may not satisfy, Dematerializing acknowledges the pleasures, along with the pitfalls, of living in a material world. With a sharp eye and an attitude that's anything but holier-than-thou, Jane Hammerslough encourages readers to explore how a consumption-crazed culture affects their own relationships with objects. By considering what possessions can and can't do, and by exploring where belief in the magic of the material encroaches on belief in ourselves and other people, Dematerializing offers insight into the pressures of living in a possession-obsessed environment-and ways to tame materialism in our own lives. Grounded by real-world examples, research, and the author's own experience, this inspiring book is for those who appreciate having "nice things" but are also disturbed by the control "nice things" sometimes have on their lives.

Customer Reviews:

Well thought-out, honest, comprehensive and sometimes even inspiring.......2005-10-27

Wonderful book. I don't know how she did it, but she seems to have organized and thoroughly analyzed the very large topic of posessions and materialism, and all in a very readable and fluid style.

I found myself often wondering how she so easily transitioned one chapter or idea to another, but it always worked somehow. Filled with helpful suggestions on how to keep one's perspective, but never preachy. She speaks with understanding and awareness, and has insights only one who could have gone, perhaps, a bit too far, could ever have. Her anecdotes are particularly interesting, as she takes elements from her own personal life and integrates them into a larger philosophical discussion.

I think one of the strongest points of the book is that it carefully and thoughtfully disects the reasons why we want things and gets to the root of the problem, while not wasting a lot of time explaining or giving advice on how we stop ourselves from wanting (come on people, the first question answers the second). And she speaks from the heart. Far from a distanced sociological paper on materialism, this book is one woman's attempt at trying to throttle back and re-evaluate what is truly important in life... and with such thorough research and a comprehensive understanding, she shares her wisdom with us. Thank you, Jane.

'Dematerialize' by avoiding this book!.......2004-12-17

The title holds promise--advice on how to break the buying habit. The contents proved to be everything but--pages of poorly-and annoyingly--written filler on why we're so consumed by consuming. After slogging through this wasteland of non-information, I gave up and turned with hope to the last chapter, the one that's supposed to offer advice. It does, but it's pathetically shallow and self-evident. Readers, the first step in dematerializing is to not waste money on this book. The next step is to gather your thoughts and come up with your own way to dematerialize. I guarantee you'll do a much better job than Hammerslough. And it won't cost you a penny.

one of the top 10 books I've ever read, and I read a lot.......2004-09-28

Original thinking. Very thorough analysis of why people buy things, or want to buy them. Looks at it from many different angles. If you spend too much, or find that spending money or having things doesn't solve your problem of wanting things (that is, do you just end up wanting more?), then this book can help you do some soul-searching to arrive at a solution. Sees possessions as symptoms, not goals. Examines why you want things, and how you can solve the problem of spending too much or putting too much emphasis on possessions by changing your thinking. Expertly written. A pleasure to read.

Thoughtful advise.......2002-05-31

Because we practice a voluntary simplicity, your money or your life way of living I am always interested in books on the subject of downsizing or decluttering or dematerializing. So this book caught my eye. I especially liked how she speaks to the issues of fear and feeling one may be deprived if they do with less. How as a society we have evolved and look to things to bring us a feeling of worth or happiness whereas in decades past it was family and friends whom we turned to. Ironically those were also the decades when people had money in savings accounts and weren't in debt. The books premise really is money cant buy you love.

I especially liked Chapter 11 where the author talks about the value of having one day (Sunday) where we don't do anything except rest and relax. And she differentiates between recreation and fun and real rest and relaxation. And she discusses developing a will for living. Doing what gives one pleasure as well as an income. And the importance of simply being thankful for what one has. I really agree with her on that. I often stand in the shower and realize that there are people who have no indoor plumbing. No hot water at the turn of a knob, and now clean clothes fresh out of a washing machine and dried and ready for me to wear. Or the fact that I turn a knob and I have hot water to wash dishes, which in turn helps prevent diseases that in so many of the worlds countries are rampant.

It is a book I recommend although I believe Your Money or Your Life is number one and the author agrees since she lists it on the books to read section.

Oversimplified and Superficial.......2002-04-30

Although I had high hopes for this book, I was disappointed by Hammerslough's mediocre analysis of consumerism in America. It may be plumped up by some interesting examples of materialism, but it fails to really identify the cultural roots of why we overspend, why we seek comfort in things.

Most dismaying is the final chapter of the book, which provides a superficial overview on how we can overcome our materialist nature. This chapter reads like a simplistic advice column from a whiny monthly magazine.

Save your money for something you really need.

Average customer rating:
Dematerializing: Taming the Power of Possessions
Jane Hammerslough
Manufacturer: Perseus Publishing
ProductGroup: Book
Binding: Paperback
ASIN: B000N7CN5K

Book Description

Evolutionary Computing is the collective name for a range of problem-solving techniques based on principles of biological evolution, such as natural selection and genetic inheritance. These techniques are being increasingly widely applied to a variety of problems, ranging from practical applications in industry and commerce to leading-edge scientific research.

This book presents the first complete overview of this exciting field aimed directly at lecturers and graduate and undergraduate students. It is also meant for those who wish to apply evolutionary computing to a particular problem or within a given application area. To this group the book is valuable because it presents EC as something to be used rather than just studied.

Last, but not least, this book contains quick-reference information on the current state-of-the-art in a wide range of related topics, so it is of interest not just to evolutionary computing specialists but to researchers working in other fields.

Customer Reviews:

Excellent textbook.......2006-10-31

I have used evolutionary programming in my research in the past and have read several books on the topic. This is one of the most well written books available, that can easily be read by a beginner despite its depth. The conclusions that they draw are logical and supported by the appropriate references. If you had to read only one book in evolutionary programming, consider this as a candidate.

Evolution as a practical tool.......2006-04-04

The authors emphasise from the get-go that this book is meant as a practical introduction to the application of evolutionary computing. It is not a high brow, abstruse monograph. (Which indeed Springer texts often are.)

The level of discussion can be adequately understood by someone with a good background in computing and hopefully also in some science or engineering field. Certainly, there are important abstractions that must be mastered. Like how the evolutionary search can be seen as a path across a fitness landscape or potential energy surface. But there appears to be a careful explanation of the minimum necessary maths to convey an idea. And where a chapter's references might point to more specialised texts or journal papers that give a fuller math treatment.

It may well be, as another reviewer remarked, that there is insufficient detail in some passages of this book. But perhaps the text is not meant to be a low level "user's manual" type of discussion.

If you do find this book useful, consider a more advanced text, "Foundations of Genetic Programming" by Langdon and Poli, also published by Springer. It takes you deeper into the subject.

Excellent introduction.......2005-02-02

I taught our introduction to evolutionary computation class from this book. It is a well rounded introduction to the topic covering most of the introductorty material you would expect. There is an real dearth of good introductory books for EC. This is probably the best because of its breadth. Its weakness is its lack of detail. It would not hurt if they covered the same material in about 50% more pages. As soon as they start a topic its over and on to the next topic. But if you are new to the field they give plenty of references and touch on most topics in enough detail for students to implement. All in all a good solid job.

An excellent textbook suitable for all levels.......2004-06-06

This is an excellent textbook which covers most aspects of the Evolutionary Computing. It's suitable for all levels. It's easy to follow, rich in content and has many references (439 to be precise) for further information. The table of contents from the book's web site is as follows:

1. Introduction
2. What is an Evolutionary Algorithm?
3. Genetic Algorithms
4. Evolution Strategies
5. Evolutionary Programming
6. Genetic Programming
7. Learning Classifier Systems
8. Parameter Control in Evolutionary Algorithms
9. Multi-Modal Problems and Spatial Distribution
10. Hybridisation with Other Techniques: Memetic Algorithms
11. Theory
12. Constraint Handling
13. Special Forms of Evolution
14. Working with Evolutionary Algorithms
15. Summary
16. Appendices
17. Index
18. References

Recommended to everyone interested in EC.

an excellent introduction.......2004-01-29

The book is easy and refreshing to read. Assuming only a minimum of prior knowledge, all the relevant aspects are covered. The focus is on practical applications, with numerous examples, simple equations and plenty of practical advise for the user.

As should be the costum with every scientific introduction, the authors are at great pains to clarify the relationship between the different flavours of EC and to show how they historically developed.

The book does not provide much on the mathematical level, though. Not even a basic graph theoretical analysis of mutation and recombination.

Book Description

Computational intelligence is the study of adaptive mechanisms to enable or facilitate intelligent behaviour in complex and changing environments. As such, computational intelligence combines artificial neural networks, evolutionary computing, swarm intelligence and fuzzy systems.

This book presents a highly readable and systematic introduction to the fundamentals of computational intelligence. In-depth treatments of the more important and most frequently used techniques are also given. The book provides treatment of computational intelligence in a manner which allows the reader to easily implement the different techniques, and to apply these techniques to solve real-world, complex problems.

Key features include:

A balanced treatment of the different computational intelligence paradigms
Inclusion of swarm intelligence
Coverage of the most recent developments in computational intelligence
Complete algorithms presented in pseudo-code to allow implementation in any language
Includes numerous exercises to involve and stimulate the reader further

The careful and considered approach to this key subject makes this book appropriate for both the first-time reader, as well as individuals already active in the field.

Customer Reviews:

Just a brief survey of what CI is. Not really a great book that teaches you the foundations of CI........2006-11-10

In ONE world: 'self-filler'
This book is not really an introduction to Computational Intelligence, for an introductory type of book read David E. Goldberg's Genetic Algorithms Book, it is exceptional in terms of readability, concepts presented and depths it gradually delves into. That is the father of all genetic algorithm/EC/AI books, in my humble opinion.

I know most of the stuff in Engelbrecht's book now, not because I've read it from his book, but because I've learnt it from other sources, do yourself a favor, read more descriptive aind insightful material about AI and CI. the chapters on NN and SOM, GA, EC are very shallow, he just summarizes ideas you can get from reading free sources like, AI webpages, presents a bunch of formulas, and to understand what they mean, you have to refer to the glossary and appendices. Furthermore he is inconsistent in his symbols, the terms represented by his symbols change through-out the book, sometimes even in consecutive chapters.

Stuff he never addresses: Taboo Search, Simulated Annealing aren't even mentioned in the book. Travelling salesman problems, snake in the box, hybrid systems, neuro fuzzy system, adaptive genetic fuzzy systems are all never mentioned. There are no examples of the uses of the material he covers, kind of takes the flavor away from what you're reading. It is bland, fonts are awful, and pictures are drawn with Microcrap's paintbrush. This book will never give you an insight into CI paradigms, if you already know that stuff and want a quick revision, or want a reference for the formulas, get this book, or else it's just a shelf-filler. [...]

A fine overview.......2003-03-05

The book is divided into four parts. The first part is about neural networks and is covered in much more depth than other parts. The author touches upon every major neural network paradigm and covers fundamental learning techniques. What bothers me about the first part is following:
- it is too theoretical
- the chapter about neural networks performance is too fat, although practical (but it would be better to be more practical about general NN techniques), so i lost interest in it when reading.
The second part about genetic algorithms is interesting and concise, but techniques like cultural evolution and coevolution are flabby explained. Few pages more could be spared.
The third part about swarm intelligence covers two techniques, namely ant colonies and particle optimization. Since there is not much literature about these young techniques, i find them quite well explained.
The last part about fuzzy logic was a bit disappointing, because it seemed like the author was in a rush to finish the book. Too shallow to be of any practical use (but still as a reference).
All in all is the book a good overview with lots of references on more specialized literature. I don't know about any other book to cover such diverse fields in one volume, and therefore recommend it for readers, who do not intend to go into deep study of things.

A good start.......2003-01-18

This book is suitable for undergraduates and first-year graduate students in computer science who are interested in getting an overview of what is and has been done in a field that used to be classified as "artificial intelligence". The new designation as "computational intelligence" was done so as to distance it from other activities in artificial intelligence that are deemed somewhat exotic, such as the efforts to build autonomous thinking machines. The book can be read very quickly, due to the sparse nature of the paragraph organization, and the author puts exercises at the end of each chapter to test the reader's insight and problem solving ability.

The author divides his book into five parts, the first one being an introduction and history, and the next four being on neural networks, evolutionary computation, swarm intelligence, and fuzzy systems. The third part is relatively new on the scene in computational intelligence, and so its inclusion in this book is welcomed.

Neural networks have been extensively used in the last four decades in many different fields, such as financial engineering, bioinformatics, physics, and network analysis. The author devotes six chapters to their elucidation, and he discusses the most important types of artificial neural networks and the different learning schemes employed by them. Detailed derivations and pseudocode are given for these, particularly for back-propagation, and the "LeapFrog" and "conjugate gradient" approaches to optimization. Most interesting is the inclusion of a "swarm optimization" technique. Although brief, the author includes pseudocode and references for further reading.

The author includes a discussion of product unit neural networks, which are sometimes not treated in other books on neural networks. In this type of neural network, the neurons compute the weighted product of the input signals, and the author includes a "distortion factor" that allows the dynamical shaping of the activiation function during the training phase. Only a cursory discussion of what it actually means for a neural network to learn is given, but references for further reading are included. The author also includes a nice discussion of performance issues in the use of neural networks. Readers who eventually use them in practice will find that neural networks can be computationally intensive. An interesting inclusion in this discussion is that of the VC-dimension, and how it relates to the total number of weights in a 1-hidden layer network, and thus of the number of training examples needed. The reader is asked to investigate the role of the Huber function in making a neural network more robust to outliers. The author cautions the reader that the use of neural networks should not be taken lightly and great care is need to insure optimal performance.

In part 3 the author treats genetic and evolutionary programming, evolutionary strategies, differential and cultural evolution, and co-evolution. The use of these techniques has dramatically increased in the last decade, especially in optimization problems. The author points out the role of finding the right chromosome representation in the design of an evolutionary algorithm, this serving also as a kind of classification of the different approaches: binary strings for genetic algorithms, tree representations for genetic programming, and real numbers for evolutionary programming. The author compares briefly the use of evolutionary computing versus using techniques from classical optimization theory, with the role played by the "no-free-lunch" theorem. The author holds that evolutionary algorithms are superior for discontinuous, nondifferentiable, multimodal, and noisy problems.

Of personal interest to me, an application of genetic algorithms to routing optimization is discussed in this part. The author also briefly mentions "niching" as a method to locate multiple minima and asks the reader to develop a genetic algorithm to train a feed-forward neural network as an exercise. For readers who have a knowledge of LISP the discussion on genetic programming will seem much more natural. Evolutionary programming, which differs from genetic algorithms and genetic programming with its omission of crossover and its emphasis on simulating adaptive behavior in evolution, and not genetic models is given ample treatment, along with some useful pseudocode. An elementary application to function optimization is given. The discussion on evolutionary strategies is a fine one since the ones in the literature may be too difficult mathematically for a reader at this level. The discussions on differential and cultural evolution, and coevolution are too brief however (only a few pages devoted to each).

Of great interest to me was the part on swarm intelligence, as my knowledge of this field is very meager. It has taken on importance recently in research circles and so I was very interested in seeing if could be used successfully in practical optimization problems. Having just begun to get my feet wet in swarm intelligence algorithms, this part was a good help in giving me more insight into the use of them. This book is one of the few that covers swarm intelligence, most of the literature still being found in online preprints and published journal articles. The author calls one approach "particle swarm optimization" (PSO), and he explains how the different social interaction schemes serve to classify the algorithm, going by the namnes of star, ring, and wheels topology. He also discusses various modifications to PSO that improve its convergence and to increase its diversity. Another approach is based on the social interaction of ants, and is called appropriately "ant colony optimization". This approach has been applied with some success to route assignment in packet networks, and has been shown to be competetive with vector-distance and link-state shortest path algorithms. It remains to be seen if such an approach will be implemented in real-world network topologies, dominated as they are currently with legacy hardware. The author also gives brief discussions on some of its other applications, such as robotics, and the quadratic assignment, job-scheduling, and graph coloring problems.

Book Description

Analysis of molecular sequence data is the main subject of this introduction to computational biology. There are two closely connected aspects to biological sequences: (i) their relative position in the space of all other sequences, and (ii) their movement through this sequence space in evolutionary time. Accordingly, the first part of the book deals with classical methods of sequence analysis: pairwise alignment, exact string matching, multiple alignment, and hidden Markov models. In the second part evolutionary time takes center stage and phylogenetic reconstruction, the analysis of sequence variation, and the dynamics of genes in populations are explained in detail. In addition, the book contains a computer program with a graphical user interface that allows the reader to experiment with a number of key concepts developed by the authors.

This textbook is intended for students enrolled in courses in computational biology or bioinformatics as well as for molecular biologists, mathematicians, and computer scientists.

Customer Reviews:

try the enclosed GUI program.......2006-10-14

For some readers, the best attraction of the book is the GUI program that lets you quickly experiment and apply the main ideas. The text is very interdisciplinary, written for diverse audiences, spanning biology, computer science and mathematics. Some aspects of the book may perhaps be too mathematical for some biology readers. Say the Hidden Markov Models, for example. But if you keep at it, you should get able to get the gist of the models. Which is another reason for the usefulness of the GUI. Essentially, so long as you understand the basic math ideas, the GUI lets you sidestep the grotty details and focus on applying the overall models.

It could also be that the book is suitable for a university course. The chapter exercises and accompanying answers are useful, in this regard.

An Introduction to Evolutionary Computation

Average customer rating:

Unique contribution for signal processing

An Introduction to Evolutionary Computation

Manufacturer: Institute of Electrical & Electronics Enginee
ProductGroup: Book
Binding: Hardcover

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ASIN: 0780346572

Book Description

Evolutionary computation is one of the fastest growing areas of computer science, partly because of its broad applicability to engineering problems. The methods can be applied to problems as diverse as supply-chain optimization, routing and planning, task assignment, pharmaceutical design, interactive gaming, and many others within the signal processing domain. The book is an outgrowth of successful SPIE short courses taught by the author. The examples span a range of applications and should be useful to a variety of readers with different backgrounds and expertise.

Customer Reviews:

Unique contribution for signal processing.......2000-10-16

The book is excellent. It provides a comprehensive description of evolutionary computation applied to almost every facet of signal processing: classification, clustering, time series, system identification, etc. The final chapter provides some real insight on how to design evolutionary algorithms that is very helpful. The material is well presented and easy to understand. I really like it and the cost is reasonable.

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