Circuit Analysis Programmes Developed for Use in Degree Circuit Theory Courses

1975 ◽  
Vol 12 (4) ◽  
pp. 293-297
Author(s):  
G. J. Hawkins

This paper describes five basic computer programmes, easy for the student or circuit designer to use, which aid and illustrate elementary circuit analysis techniques. Programmes may be stored in the computer library so permitting the minimum number of control instructions, and thus the data entry is very simple.

Author(s):  
Christof Koch

The brain computes! This is accepted as a truism by the majority of neuroscientists engaged in discovering the principles employed in the design and operation of nervous systems. What is meant here is that any brain takes the incoming sensory data, encodes them into various biophysical variables, such as the membrane potential or neuronal firing rates, and subsequently performs a very large number of ill-specified operations, frequently termed computations, on these variables to extract relevant features from the input. The outcome of some of these computations can be stored for later access and will, ultimately, control the motor output of the animal in appropriate ways. The present book is dedicated to understanding in detail the biophysical mechanisms responsible for these computations. Its scope is the type of information processing underlying perception and motor control, occurring at the millisecond to fraction of a second time scale. When you look at a pair of stereo images trying to fuse them into a binocular percept, your brain is busily computing away trying to find the “best” solution. What are the computational primitives at the neuronal and subneuronal levels underlying this impressive performance, unmatched by any machine? Naively put and using the language of the electronic circuit designer, the book asks: “What are the diodes and the transistors of the brain?” and “What sort of operations do these elementary circuit elements implement?” Contrary to received opinion, nerve cells are considerably more complex than suggested by work in the neural network community. Like morons, they are reduced to computing nothing but a thresholded sum of their inputs. We know, for instance, that individual nerve cells in the locust perform an operation akin to a multiplication. Given synapses, ionic channels, and membranes, how is this actually carried out? How do neurons integrate, delay, or change their output gain? What are the relevant variables that carry information? The membrane potential? The concentration of intracellular Ca2+ ions? What is their temporal resolution? And how large is the variability of these signals that determines how accurately they can encode information? And what variables are used to store the intermediate results of these computations? And where does long-term memory reside? Natural philosophers and scientists in the western world have always compared the brain to the most advanced technology of the day.


FLORESTA ◽  
2019 ◽  
Vol 49 (2) ◽  
pp. 305
Author(s):  
Bruno Oliveira Lafetá ◽  
Tamires Mousslech Andrade Penido ◽  
Nivaldo De Souza Martins ◽  
Márcio Leles Romarco de Oliveira ◽  
Danielle Piuzana Mucida ◽  
...  

Information about sample adequacy that represents soil chemical attributes distribution are fundamental for a better rationalization of the use of correctives and fertilizers. The objective was to evaluate the variability of these attributes and to size the minimum number of composite samples to represent the fertility of forest soils. The total area planted was 9,101ha, constituted of 265 commercial eucalypt stands. The 687 soil composite samples obtained were for chemical analysis. It was evaluated the performance of two exploratory analysis techniques and six sampling procedures. The attributes P, K, Ca, Mg and S presented higher coefficient of variation (>35%). In contrast, the distributions of Al, organic matter and, mainly, pH were the most homogeneous. The sample error was smaller as the amount of composite samples increased. The representative of all chemical attributes (sample error of 5%) was achieved with a minimum of 309 (one each 29ha, 1:29) and 295 (1:31) composite samples from sampling procedures simple casual and stratified by altitude class, respectively. Both procedures were promising for soil sampling, especially, when applying the boxplot for identification and removal of outliers.


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