miércoles, 29 de octubre de 2014

Aprender de Circuito en AC, Circuitos Frecuencia

http://www.learnabout-electronics.org/ac_theory/filters81.php

Passive Filters

What you´ll learn in Module 8.1

  • After studying this section, you should be able to describe:
  • • Uses for passive filters
  • • Typical filter circuits.
  •   • RC filters.
  •   • LC filters.
  •   • LR filters.
  • Recognise packaged filters.
  •   • Ceramic filters.
  •   • SAW filter.
  •   • Three−wire encapsulated filters.

Uses for passive filters.

Filters are widely used to give circuits such as amplifiers, oscillators and power supply circuits the required frequency characteristic. Some examples are given below. They use combinations of R, L and C
As described in Module 6, Inductors and Capacitors react to changes in frequency in opposite ways. Looking at the circuits for low pass filters, both the LR and CR combinations shown have a similar effect, but notice how the positions of L and C change place compared with R to achieve the same result. The reasons for this, and how these circuits work will be explained in Section 8.2 of this module.

Low pass filters.

LR Low pass filter RC Low pass filter Low pass filters are used to remove or attenuate the higher frequencies in circuits such as audio amplifiers; they give the required frequency response to the amplifier circuit. The frequency at which the low pass filter starts to reduce the amplitude of a signal can be made adjustable. This technique can be used in an audio amplifier as a "TONE" or "TREBLE CUT" control. LR low pass filters and CR high pass filters are also used in speaker systems to route appropriate bands of frequencies to different designs of speakers (i.e. ´ Woofers´ for low frequency, and ´Tweeters´ for high frequency reproduction). In this application the combination of high and low pass filters is called a "crossover filter".
Both CR and LC Low pass filters that remove practically ALL frequencies above just a few Hz are used in power supply circuits, where only DC (zero Hz) is required at the output.

High pass filters.

LR High pass filter RC High pass filter High pass filters are used to remove or attenuate the lower frequencies in amplifiers, especially audio amplifiers where it may be called a "BASS CUT" circuit. In some cases this also may be made adjustable.

Band pass filters.

LC Bandpass filter Band pass filters allow only a required band of frequencies to pass, while rejecting signals at all frequencies above and below this band. This particular design is called a T filter because of the way the components are drawn in a schematic diagram. The T filter consists of three elements, two series−connected LC circuits between input and output, which form a low impedance path to signals of the required frequency, but have a high impedance to all other frequencies.
Additionally, a parallel LC circuit is connected between the signal path (at the junction of the two series circuits) and ground to form a high impedance at the required frequency, and a low impedance at all others. Because this basic design forms only one stage of filtering it is also called a ´first order´ filter. Although it can have a reasonably narrow pass band, if sharper cut off is required, a second filter may be added at the output of the first filter, to form a ´second order´ filter.

Band stop filters.

LC Bandstop filter These filters have the opposite effect to band pass filters, there are two parallel LC circuits in the signal path to form a high impedance at the unwanted signal frequency, and a series circuit forming a low impedance path to ground at the same frequency, to add to the rejection. Band stop filters may be found (often in combination with band pass filters) in the intermediate frequency (IF) amplifiers of older radio and TV receivers, where they help produce the frequency response curves of quite complex shapes needed for the correct reception of both sound and picture signals. Combinations of band stop and band pass filters, as well as tuned transformers in these circuits, require careful frequency adjustment.
IF Transformer

I.F. Transformers.

These are small transformers, used in radio and TV equipment to pass a band of radio frequencies from one stage of the intermediate frequency (IF) amplifiers, to the next. They have an adjustable core of compressed iron dust (Ferrite). The core is screwed into, or out of the windings forming a variable inductor.
This variable inductor, together with a fixed capacitor ´tunes´ the transformer to the correct frequency. In older TV receivers a number of individually tuned IF transformers and adjustable filter circuits were used to obtain a special shape of pass band to pass both the sound and vision signals. This practice has largely been replaced in modern receivers by packaged filters and SAW Filters.

Packaged Filters.

There are thousands of filters listed in component catalogues, some using combinations of L C and R, but many making use of ceramic and crystal piezo-electric materials. These produce an a.c. electric voltage when they are mechanically vibrated, and they also vibrate when an a.c. voltage is applied to them. They are manufactured to resonate (vibrate) only at one particular, and very accurately controlled frequency and are used in applications such as band pass and band stop filters where a very narrow pass band is required. Similar designs (crystal resonators) are used in oscillators to control the frequency they produce, with great accuracy. One packaged filter in TV receivers can replace several conventional IF transformers and LC filters. Because they require no adjustment, the manufacture of RF (radio frequency) products such as radio, TV, mobile phones etc. is simplified and consequently lower in price. Sometimes however, packaged filters will be found to have an accompanying LC filter to reject frequencies at harmonics of their design frequency, which ceramic and crystal filters may fail to eliminate.

TV SAW Filter

SAW filters The illustration (right) shows a Surface Acoustic Wave (SAW) IF (intermediate frequency) filter for PAL TV. SAW filters can be manufactured to either a very narrow pass band, or a very wide band with a complex (pass and stop) response to several different frequencies. They can produce several different signals of specific amplitudes at their output. Special TV types replace several LC tuned filters in modern TVs with a single filter. They work by creating acoustic waves on the surface of a crystal or tantalum substrate, produced by a pattern of electrodes arranged as parallel lines on the surface of the chip. The waves created by one set of transducers is sensed by another set of transducers designed to accept certain wavelengths and reject others.
SAW Filter information from ITF of Korea
Saw Filters by Epcos
Saw filters are produced for many different products and have response curves tailored to the requirements of specific types of product.

Ceramic Filters

Ceramic Filter Ceramic Filter Symbol Ceramic filters are available in a number of specific frequencies, and use a tiny block of piezo electric ceramic material that will mechanically vibrate when an a.c. signal of the correct frequency is applied to an input transducer attached to the block. This vibration is converted back into an electrical signal by an output transducer, so only signals of a limited range around the natural resonating frequency of the piezo electric block will pass through the filter. Ceramic filters tend to be cheaper, more robust and more accurate than traditional LC filters for applications at radio frequencies. They are supplied in different forms including surface mount types, and the encapsulated three pin package shown here.

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sábado, 25 de octubre de 2014

EL PROBLEMA DE JOSEPHUS







EL PROBLEMA DE JOSEPHUS
Números
 
http://recursostic.educacion.es/descartes/web/materiales_didacticos/problema_josephus/ProblJosephus.htm

EL PROBLEMA DE JOSEPHUS
Cuenta una leyenda sobre el historiador Josephus Flavius que, durante las guerras judeo-romanas, él y otros 40 soldados judíos quedaron atrapados en una cueva rodeados por los romanos.  Visto que tenían pocas posibilidades de salir con vida, decidieron suicidarse. Josephus y un amigo suyo no estaban muy felices con esa idea. Así pues, propusieron que si había que hacerlo, se hiciera con cierto orden: se colocarían en círculo y se irían suicidando por turno cada tres empezando a contar por uno determinado.
Josephus y su amigo se colocaron de tal forma que fueron los dos últimos y así, como ya nadie les podía llevar la contraria, decidieron seguir viviendo.
La escena que sigue servirá para simular esta historia, olvidándonos del amigo. Se trata de colocar a Josephus (punto amarillo) en la posición adecuada para que sea el único superviviente. Una vez se haya colocado a Josephus, pulsando sobre <Animar> se irán "suicidando" los puntos verdes (pasarán a rojo). Se empieza a contar desde el punto superior de la escena, éste será el número uno, siguiendo el sentido de las agujas del reloj. El primero en caer será el número 3, luego el número 6, ... El control "mseg" permite acelerar o no la animación.
Este problema se puede generalizar fácilmente a un número distinto de 41 y a un paso distinto de 3. El número mínimo de soldados judíos que se permite en esta simulación es 4 y el máximo, 80; y para el "paso", cualquier valor entero comprendido entre 1 y 99999. Al pulsar sobre el botón "Nuevo" estará listo nuestro nuevo problema.
En Internet se puede encontrar mucha literatura sobre este problema, tanto en inglés como en español. En español también se le conoce con el nombre de "El problema de José".


Número de soldados: Paso:

Salvador Calvo-Fernández Pérez


Ministerio de Educación, Cultura y Deporte. Año 2004





Licencia de Creative Commons
Los contenidos de esta unidad didáctica están bajo una licencia de Creative Commons si no se indica lo contrario.

Habilitar java en windows 8 Java Control Panel


https://www.java.com/en/download/help/win_controlpanel.xml

 

 Java Control Panel

  • Click Windows Start button.
  • In the Start Search box, type:
    Windows 32-bit OS: c:\Program Files\Java\jre7\bin\javacpl.exe
    Windows 64-bit OS: c:\Program Files (x86)\Java\jre7\bin\javacpl.exe
  •  
  •  
  •  
  •  
  •  
  • Where is the Java Control Panel on Windows?


    This article applies to:
  • Platform(s): Windows 8, Windows 7, Vista, Windows XP, Windows 2000, Windows 2003, Windows 2008 Server, Windows ME, Windows 2012 Server


Find the Java Control Panel - Java 7 Update 40 (7u40) and later versions

Starting with Java 7 Update 40, you can find the Java Control Panel through the Windows Start menu.
  1. Launch the Windows Start menu
  2. Click on Programs
  3. Find the Java program listing
  4. Click Configure Java to launch the Java Control Panel

Find the Java Control Panel - Versions below 7u40

Windows 8
Use search to find the Control Panel
  1. Press Windows logo key + W to open the Search charm to search settings
    OR
    Drag the Mouse pointer to the bottom-right corner of the screen, then click on the Search icon.
  2. In the search box enter Java Control Panel
  3. Click on Java icon to open the Java Control Panel.
Windows 7, Vista
  1. Click on the Start button and then click on the Control Panel option.
  2. In the Control Panel Search enter Java Control Panel.
  3. Click on the Java icon to open the Java Control Panel.
Windows XP
  1. Click on the Start button and then click on the Control Panel option.
  2. Double click on the Java icon to open the Java Control Panel.

Java Control Panel

Alternate method of launching Java Control Panel

  • Click Windows Start button.
  • In the Start Search box, type:
    Windows 32-bit OS: c:\Program Files\Java\jre7\bin\javacpl.exe
    Windows 64-bit OS: c:\Program Files (x86)\Java\jre7\bin\javacpl.exe

  •  

Libros

http://www.eboooooook.com/Upload/

Index of /Upload

El reproductor de gifs

http://ludoforum.com/el-reproductor-de-gifs.html

El reproductor de gifs




El diseñador Pierterjan Grandry a creado un dispositivo que es capaz de reproducir un gif animado.

Un gif animado es un formato de archivo digital, en el que varias imágenes se muestran en un bucle una detras de otra, la creando una película de pequeño tamaño. Este tipo de archivo se introdujo por primera vez en 1987 como película en línea, pero pronto perdió su función original debido al aumento de la velocidad de Internet y la posibilidad de subir películas con mayor tamaño y calidad. El tipo de documento sin embargo, ha recuperado parte de su popularidad e incluso entrar en el campo del arte actual.


En 1832, Jozeph Plateau, físico belga, inventó el fenaquistiscopio. El primer dispositivo que fue capaz de mostrar una imagen en movimiento y que se considera que es la precursor del cine moderno. El único defecto del fenaquistiscopio, fue el hecho de que sólo podía ver pequeñas películas en un bucle. Un gif animado es exactamente eso, una película en bucle. Por eso, basándose en el diseño original de Plateau, Grandry ha logrado construir un dispositivo capaz de reproducir gifs animados, incorporando luces LED, microchips y sensores magnéticos.


El reproductor Gif es una caja de madera, muy similar a un tocadiscos, con un regulador para ajustar la velocidad de la animación y un pequeño agujero para mirarlo de frente.
Si eres un manitas puedes encontrar un guia detallada de como hacer este dispositivo, aquí.

Como hacer un persona o una imagen con curvas parametricas matematicamente y luego plot How to create a new “person curve”?

http://mathematica.stackexchange.com/questions/17704/how-to-create-a-new-person-curve
Wolfram|Alpha has a whole collection¹ of parametric curves that create images of famous people. To see them, enter WolframAlpha["person curve"] into a Mathematica notebook, or person curve into Wolfram|Alpha. You get a mix of scientist, politicians and media personalities, such as Albert Einstein, Abraham Lincoln and PSY: people
The W|A parametric people curves are constructed from a combination of trigonometric and step functions. This suggests that the images might have been created by parametrising a sequence of contours... which is backed up by some curves being based of famous photos, e.g., the W|A curve for PAM Dirac:
enter image description here
is clearly based on the Dirac portrait used in Wikipedia:
enter image description here
Here's a animation showing each closed contour of Abraham Lincoln's portrait as the plot parameter t increases by 2π units:
Animated Abe
Since the functions are so complicated, I can't believe that they were manually constructed. For example, the function to make Abe's bow tie is (for 8π<t<10π) {x,y}=...
The full parametric curve for Abe has 56 such curves tied together with step functions and takes many pages to display.
So my question is:
How can I use Mathematica to take an image and produce a good looking "people curve"?
Answers can start from line art and just automatically parametrise the lines or they can start from a picture/portrait and identify a set of contours that are then parametrised. Or any other (semi)automated approach that you can think of.
¹ At the time of posting this question, it has 37 such curves.
shareimprove this question

    
Could you please explain why you "can't believe that these were hand written"? –  belisarius Jan 13 '13 at 4:57
    
@belisarius: I've added an example of part of the output from WolframAlpha["Abraham Lincoln curve", {{"EquationsPod:PlaneCurve", 1}, "FormulaData"}]. Not even the most downtrodden intern would be able to hand write such a mathematical function. Although, I admit, it could be hand traced and the traces parametrised - thus the line art comment in my question. –  Simon Jan 13 '13 at 5:14
2  
Given that the coefficients of t inside the sinusoids are 1, 2, 3, ..., this is probably just the Fourier representation of a parametric curve. I'd guess they manually traced the curve as a polygon, took the discrete Fourier transform, and kept just enough of the lowest-order modes to make the curve look right. See also: Ptolemy and Homer (Simpson). –  Rahul Narain Jan 13 '13 at 5:32
1  
Another demonstration: TracingContourLinesInPhotographicImages gets a handle on contour lines. –  Michael E2 Jan 13 '13 at 14:11
1  
The method called "Fourier Descriptors" does something similar: demonstrations.wolfram.com/preview.html?draft/46249/000012/… –  bill s Jan 13 '13 at 17:37

3 Answers

up vote 20 down vote accepted
This now has been discussed in Wolfram blog posts by Michael Trott:
Part 1: Making Formulas… for Everything — From Pi to the Pink Panther to Sir Isaac Newton
Part 2: Using Formulas... for Everything — From Complex Analysis Class to Political Cartoons to Music Album Covers
Here is one of the example apps from blog - go read it in full - fun! Don't miss the link to download the notebook with complete code and apps at the end of the blog.
Newton Outline Manipulable
shareimprove this answer

7  
Nice picture of Newton. But why does his shirt have so many buttons? –  Daniel Lichtblau May 17 '13 at 19:36
3  
@DanielLichtblau Newton was known to dress up in disguises and roam the streets of London in order to catch the counterfeiters. As Warden, and afterwards Master, of the Royal Mint, Newton estimated that 20 percent of the coins taken in during The Great Recoinage of 1696 were counterfeit. Counterfeiting was high treason, punishable by the felon's being hanged, drawn and quartered. Despite this, convicting the most flagrant criminals could be extremely difficult. However, Newton proved to be equal to the task. Disguised as a habitué of bars and taverns, he gathered much of that evidence himself. –  Vitaliy Kaurov May 17 '13 at 19:49
3  
Ironically, it was Newton himself who was drawn above. In portrait form, suitable for hanging in ones quarters. But I digress. –  Daniel Lichtblau May 17 '13 at 20:33
This shows a way to parametrise a line using the method suggested by Rahul Narain in a comment, i.e. using Fourier to approximate the data with a set of sinusoids. I use Rationalize to convert all the reals back to rationals, this isn't necessary but it makes the expression look more like those used in Wolfram Alpha.
param[x_, m_, t_] := Module[{f, n = Length[x], nf},
  f = Chop[Fourier[x]][[;; Ceiling[Length[x]/2]]];
  nf = Length[f];
  Total[Rationalize[
     2 Abs[f]/Sqrt[n] Sin[Pi/2 - Arg[f] + 2. Pi Range[0, nf - 1] t], .01][[;; Min[m, nf]]]]]

tocurve[Line[data_], m_, t_] := param[#, m, t] & /@ Transpose[data]
tocurve will take a Line, a number of modes m and a symbolic parameter t and return a parametrisation of the line data. Because of the implied periodicity of the data in Fourier it will only work properly on closed lines.
The hard part is getting a good set of lines from the image of a person. Here's a much simpler example using ListContourPlot to extract the outline of a silhouette.
First load an image and do a bit of preprocessing to ensure a nice contour:
img = Import[
   "http://catclipart.org/wp-content/uploads/2012/11/elephant-silhouette-clip-art.gif"];

img = Binarize[img~ColorConvert~"Grayscale"~ImageResize~500~Blur~3]~Blur~3;
enter image description here
Now extract contours and plot the parametrised curve with 500 modes:
lines = Cases[Normal@ListContourPlot[Reverse@ImageData[img], Contours -> {0.5}], _Line, -1];

ParametricPlot[Evaluate[tocurve[#, 500, t] & /@ lines], {t, 0, 1}, Frame -> True, Axes -> False]
enter image description here
With fewer modes the detail starts to smooth out. Here's the 30 mode curve:
enter image description here
The parametrisation consists of sinusoids:
curves // Short
enter image description here
shareimprove this answer

    
That is pretty impressing! May I ask where curves comes from? –  Stefan Jan 28 '13 at 18:26
This was supposed to be a comment to Simon's answer, but it's gotten too long. Still, I wanted to share a somewhat cleaned-up version of Simon's Fourier-fitting function param[] (which I have renamed to FourierCurve[]):
FourierCurve[x_, m_, t_, tol_: 0.01] := Module[{rat = Rationalize[#, tol] &, fc},
  fc = Take[Chop[Fourier[x, FourierParameters -> {-1, 1}]], Min[m, Ceiling[Length[x]/2]]];
  2 rat[Abs[fc]].Cos[Pi (2 Range[0, Length[fc] - 1] t - rat[Arg[fc]/Pi])]]
This has the virtue of returning a function that genuinely closes up; more precisely, if f[t_] = FourierCurve[pts, modes, t], then f[0] == f[1]. (The indiscriminate use of Rationalize[] in the earlier version prevented a nice closure of the resulting curve.)
As Rahul alludes to in his comment, this is more or less the "epicycle" approach of Ptolemy for determining the paths of planetary orbits.

Of course, Fourier fitting can also be applied to space curves as well as plane curves. Here's an example:
{f[t_], g[t_], h[t_]} = FourierCurve[#, 20, t] & /@
                        KnotData["FigureEight", "SpaceCurve"]["ValuesOnGrid"];

ParametricPlot3D[{f[t], g[t], h[t]}, {t, 0, 1}, Axes -> None, Boxed -> False,
                 Method -> {"TubePoints" -> 20}, PlotStyle -> Blue, ViewPoint -> Top] /. 
Line[pts_, rest___] :> Tube[pts, 1/8, rest]
figure-eight knot
Since most of the knots given in KnotData[] have their space curves given as InterpolatingFunction[] objects, you can use this approach if you prefer to have explicit parametric expressions for those knots.
shareimprove this answer

1  
(This isn't yet my official return; I found some spare time and decided to exploit it.) –  J. M. Feb 7 '13 at 2:53
    
Spare time is hard to come by sometimes... I'll find some one day and come back to evaluating and accepting one of these answers –  Simon Apr 22 '13 at 10:35

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