The gradient descent algorithm is generally very slow because it requires small learning rates for stable learning. The momentum variation is usually faster than simple gradient descent, because it allows higher learning rates while maintaining stability, but it is still too slow for many practical applications. These two methods are normally used only when incremental training is desired. You would normally use Levenberg-Marquardt training for small and medium size networks, if you have enough memory available. If memory is a problem, then there are a variety of other fast algorithms available. For large networks you will probably want to use trainscg or trainrp.
Multilayered networks are capable of performing just about any linear or nonlinear computation, and can approximate any reasonable function arbitrarily well. Such networks overcome the problems associated with the perceptron and linear networks. However, while the network being trained might theoretically be capable of performing correctly, backpropagation and its variations might not always find a solution
This type of algorithm is commonly used in n dimensional clustering applications. This mean is commonly the simplest to use and a typical algorithm employing the minimum square error algorithm can be found in McQueen 1967.
It can cause abnormal program termination or invalid results.
Algorithms do not accept user input; they are not computer programs. All input to an algorithm is specified at the start of the algorithm along with any required preconditions and postconditions. If a required precondition is not specified or is specified incorrectly, then this could result in unexpected results (or undefined behaviour in programming terminology). The type of error in the algorithm is simply that the precondition was not specified.
1.robust 2.correct 3.optimal 4.error free 5.reliable
If you're wondering about the "Bresenham line algorithm", it is an algorithm (a process used for making a desired result) that plots a geometrical line (consiting of infinate points, as if you draw a straight line on a piece of paper) and translates it to a computer screen (composed of pixels, or video "points" that have a specific amount of sized points) The algorithm is as follows: function line(x0, x1, y0, y1)boolean steep := abs(y1 - y0) > abs(x1 - x0)if steep thenswap(x0, y0)swap(x1, y1)if x0 > x1 thenswap(x0, x1)swap(y0, y1)int deltax := x1 - x0int deltay := abs(y1 - y0)int error := -(deltax + 1) / 2int ystepint y := y0if y0 < y1 then ystep := 1 else ystep := -1for x from x0 to x1if steep then plot(y,x) else plot(x,y)error := error + deltayif error ≥ 0 theny := y + ysteperror := error - deltax This algorithm was taken from the site http://en.wikipedia.org/wiki/Bresenham's_line_algorithm
A backpropagation is an error correction technique used in neural networks.
This type of algorithm is commonly used in n dimensional clustering applications. This mean is commonly the simplest to use and a typical algorithm employing the minimum square error algorithm can be found in McQueen 1967.
Michael D. Boldin has written: 'An efficient, three-step algorithm for establishing error-correction models with an application to the U.S. macroeconomy' -- subject- s -: Macroeconomics, Econometric models
It can cause abnormal program termination or invalid results.
Algorithms do not accept user input; they are not computer programs. All input to an algorithm is specified at the start of the algorithm along with any required preconditions and postconditions. If a required precondition is not specified or is specified incorrectly, then this could result in unexpected results (or undefined behaviour in programming terminology). The type of error in the algorithm is simply that the precondition was not specified.
One of the most common reasons for getting a server application unavailable error is mixing dot NET framework. The error usually shows up when the Application Pool does not start.
Error handling refers to the anticipation, detection, and resolution of programming, application, and communications errors.
1)transcription errors. 2)computation errors. 3)algorithm errors.
1.robust 2.correct 3.optimal 4.error free 5.reliable
hey boss , its a component error! send a mail to application guy
20000 to 20099.
The algorithm used in 8 queens problem is "Backtracking"Backtracking involves trial and error , where we try all the possibilities , if a trial leads to an error we eliminate it and also no two trials can be the same.Backtracking assumes that the problem is finite and is computable within the limitations of hardware.