A linear scale is much more simple to use and provides accurate readings it also works faster than the non-linear scale . This scale does not take much work and has equal divisions.
In a linear scale, there is an equal amount between each mark; this is the normal kind of scale that is used in most everyday graphs/charts.
In a non-linear scale, the difference between each mark is not the same, for example each mark, although the same distance apart on the paper, represents twice the value of the previous mark. Two examples which are met regularly are logarithmic in nature: pH (acid/alkali scale - eg pH balanced shampoo) and dB (deci-Bel - relative loudness of sounds).
Nonlinear scaling is a scaling where the difference between each major unit of measure is not the same. For example, see logarithmic scale.
There must be a linear scale on the axes, so the even marks must have a constant difference between them. Such usual differences are 1, 5, 10, 50, etc.
On a linear scale, if two pairs of points are the same distance apart, their magnitudes differ by the same amount. So if distance from point A to B is the same as the distance from point C to D, then the magnitude of B-A is the same as D-C. On a non-linear scale this does not apply. On a logarithmic scale, for example, equal distances, as above would imply that B/A = D/C
There is no difference between the long scale million and a short scale million. There is a difference between the billion in these two scales. The American use the short scale so 1 billion to them is 1,000,000,000 or 10^9. We used to use the long scale so 1 billion is 1,000,000,000,000 or 10^12. It should be noted that for simplicity reasons especially with currency the UK have switched to the short scale system as well.
if two polygons are similar, then the ratio of the length of 2 corresponding sides is called a scale factor
The differences between the these two is that linear scale shows the relation between the map distance and the ground distance. The nonlinear scale do not show the relation between the map distance and the ground distance.
this is dumb
Nonlinear scaling is a scaling where the difference between each major unit of measure is not the same. For example, see logarithmic scale.
You can measure things with a linear scale. Practically impossible with a non-linear scale.
A linear scale is a scale with equal divisions for equal vales, for example a ruler. A non linear scale is where the relationship between the variables is not directly proportional.
Linear is a straight line and non linear could be a curve or anything but a straight line
A scale that is nonlinear. ~
The difference between linear and non-linear PCM is LPCM represents sample amplitudes on a linear scale. LPCM specifies that the values stored are proportional to the amplitudes, rather than representing say the logarithm of the amplitude or being related in some other manner. While non-linear each step size may vary in amplitude.
linear: LINE example--- line non-linear: not a LINE example--- parabola The other possibility is a graph with a non-linear scale. First a linear scale will have each unit represent the same amount, regardless of where you are on the scale. A semilog scale, has a linear scale in the horizontal direction, and a logarithmic scale in the vertical direction. Exponential functions (such as ex & 10x), will graph as a straight line on this type of graph scale). A logarithmic or log-log scale, has logarithmic scales on both horizontal and vertical axis. Power functions (such as sqrt(x), x2 and x3), graph as a straight line on these scales. See Related Link
A non-linear temperature scale means that the intervals between temperature readings are not consistent across the scale. This can result in the temperature difference between two points not being proportional to the numerical value assigned to those points on the scale. An example of a non-linear temperature scale is the Fahrenheit scale, where the degree intervals are not uniform.
To convert a direct statement scale to a linear scale, assign numerical values to the categories or statements on the direct statement scale. Then, plot these values on a linear scale, ensuring that the spacing between values is consistent to create a linear relationship between the categories or statements.
In general all systems are nonlinear but we simplify this nonlinear vibration to linear ones so that we can get approximate results. Approximate results are still good results in many cases. For example when you analyze the vibrations of the simple pendulum for small vibrations you don't need to include aerodynamic drag which is a nonlinear in its nature. By neglecting the nonlinear parts we can derive the second order differential equations which describes the motion of the system in this case gives linear vibration of simple pendulum. Another good example would be an examination of system which consists of block of mass m, spring with stiffness k and viscous damper with damping coefficient c and let's say that the block of mass m is in contact with the surface. Now the spring stiffness and the viscous damping are in reality nonlinear but for small vibration we assume they are linear. The bloc of mass m is in contact with the surface so that means that between the block and the surface is a friction. So if we analyze this system with nonlinear terms we would need to include the nonlinear stiffness, nonlinear damping coefficient and nonlinear friction. These would result in the time consuming calculation and in the end the results would little more precise than the approximation. In nonlinear analysis we attack the differential equation which describes the motion of nonlinear system with small parameter and with this we expand the solution. This method is called perturbation method. To solve nonlinear systems you need to use specific perturbation method and these methods are: Straightforward expansion, domain perturbation, multiple scale analysis etc. For more information check my site Linear Vibration.