Noise is a red rose that grows in a cornfield. It is a signal that does not belong there.This excerpt from the first chapter of Kosko's book gives you a good idea of both the subject he covers in his book and his writing style. Somewhere within the relaxed verbiage that make up the 160 pages of Noise is a good 50 page discussion of the concept of noise, examples of how it is manifest in the sciences - particularly in information theory - how different types of noise are characterized (as measurements of frequency magnitude ), how noise can be overcome, and how it can be useful in enhancing the intelligibility of a signal (a concept known as stochastic resonance). The trouble is, Kosko's writing is a little, well, noisy.
Noise is a signal we don't like.
Noise has two parts. The first has to do with the head and the second with the heart.
The first part is the scientific or objective part: Noise is a signal. But then what is a signal? A mathematical answer is that a signal is what we describe with a variable such as x. The broad answer lets light or dollars or red blood cells count as signals because they can vary in time or space.
A physical answer deals with energy.
A signal is a source of energy such as an electrical pulse or a chemical pattern or the acoustical roar of an audience. It is structured energy... Yet we see a signal as still more than energy.
A signal is anything that conveys information.
All fields of science search for signals. Physicists look for particle signals in bubble chambers. Geologists look for earthquake signals in crust data. Botanists look for hormone signals in a pruned peach branch. Political scientists look for voter signals in polls and election an results. Psychologists look for mating signals in barroom behavior and underarm sweat. Neuroscientists look for electrochemical signals in the bast synaptic webs of our brains.
The same holds for engineering but with a key difference: Engineers shape signals as well as search for them...
The second part of noise is the subjective part: It deals with values. It deals with how we draw the fuzzy line between good signals and bad signals. Noise signals are bad signals. They are the unwanted signals that mask or corrupt our preferred signals... But for whom are they bad?.. One person's signal is another person's noise...
Kosko's excitement for his subject comes through loud and clear, but the flood this unleashes tends to diffuse his writing. When one good example will do six are offered. When he intends to organize a reader's thinking, as he did in dividing noise into two parts: 'head' and 'heart,' that will define an argument in the ensuing pages, he cannot resist a tangent. Above, following a paragraph of examples of noise in different sub-areas of science, is another paragraph about how engineers are different from other scientists. Once he returns to the second half of his organizing structure, I had forgotten that I was supposed to organize my thinking into two halves.
Kosko is not merely effusive on the sentence by sentence level. The book makes five or six excellent points, but these would realistically make up a lengthy article. To fill out the longer book format, each chapter is padded with nine epigraphs. These make the same points made in the chapter, only more succinctly. In addition, Kosko repeats material unnecessarily in the body of the text. For instance, he covers stochastic resonance very adequately with good examples and a clear image in an early chapter. There is no need to cover it again toward the end of the book.
Lastly, I'm not sure if the writer or his editor were clear about what audience they were writing for. One the one hand, Kosko maintains a chatty style, offering very approachable examples for tough to understand concepts - this is a talent that makes me understand why he might have written a book on such a subject for the lay-reader. He is also great at the perfect three-sentence description of a key scientific concept to orient his reader. There is an excellent one on photosynthesis, where he characterizes humans as sugar parasites. I think it might be more accurate to say plant parasites, since as a living organism that is the source of our sugar and oxygen, plants are our host, but that's a quibble. He's also good at dropping entertaining anecdotes related to the idea of interest - like film actress Heddy Lamar's 1942 patent for a frequency-hopping spread spectrum (no...really). However, in the discussing power laws of statistics gets blinded by his own facility with mathematics in a way that would leave the average reader in the dust.
The scheme says that the noise is white if the noise spectrum does not depend explicitly on the frequency f. That corresponds to the case of 1/f raise to the power zero because the zeroth power gives the constant value of unity: 1/f0 = 1. Pink noise falls off or decreases with the inverse of the frequency. So pink noise has a spectrum that falls off with the first power of the frequency or 1/f.Or he writes one of those mind-boggling waterfalls of terminology that physicists like to think explain the universe but always make me feel like I fell down a hole and hit my head:
The earth would form a black hole if we somehow compressed it down to the size of about a marble. That would cross the critical limit where the dense object's gravity would in effect turn in on itself and suck all its matter down to a point or "singularity." A marble-size black region or event horizon would surround the infinitesimal singularity in the space-time continuum. The sun is not massive enough to become a black hole when it burns up the hydrogen in its core in about five billion years. It will instead expand into a red giant and then cool off and die quietly as a white dwarf. The sun would become a black hole if we could compress it to a dense ball with a radius of about one kilometer.Red giant. White dwarf. Right. Crystal clear.
Noise is an exercise in contradictions. I find its subject matter fascinating to think about, but the discussion goes on a bit longer than the raw material permits. The writing alternates between technical and colloquial, embedding the information in what I would say is too little context for the engineer and too much noise for the lay reader.