Products - Page: 8 of 9

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DACI DACI DACI DACI DACI DACI DACI DACI DACI DACI DACI
DACI
DACI
DACI
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DACI DACI DACI DACI DACI DACI DACI DACI DACI DACI DACI DACI DACI DACI DACI DACI DACI DACI DACI DACI DACI DACI DACI DACI DACI DACI DACI DACI DACI DACI
DACI
DACI
DACI DACI DACI DACI DACI
DACI
DACI DACI DACI DACI DACI DACI DACI

The three questions above embody the heart of design validation. Will my design work? (Verify functional and stress margins; catch design defects before they get into production; identify problems that can easily be missed by testing and simulations.) Are detected design deficiencies significant? (Risk assessment, prevent costly overdesign.) How do I correct or center my design? (Design optimization for better yield.)

We could provide examples of how Design Master does all of the above and more, but since we offer a money-back guarantee it's easier for you to get a copy of Design Master and evaluate it for yourself. You can also check the testimonials we've received from satisfied users.

If you're saying, "How can I understand a complex design without using a simulator?" you're on the wrong design wavelength. If a design is so complex that you think you need a simulator, you're asking for trouble.

Successful designs are characterized by being elegant and thereby relatively easy to understand. As you develop your analysis skills, you'll find that what initially appears to be a large complex design can often be broken into small manageable chunks for analysis.

Using Design Master, however, one identifies the boundaries of performance, then obtains an estimate of how these boundaries will exceed specification limits. This is much safer and simpler. First you identify the worst case performance boundaries, so you don't have to infer anything. This is safe. Second, using conservative assumptions, you estimate how often the calculated results will exceed the specification limits. This is simpler.

One of Design Master 's neatest features is its probability-estimating capability. This allows you to apply in a painless manner some of the powerful concepts you dreaded to study in college.

With a conventional approach, such as Monte Carlo, IF you have an adequate sample size and IF the samples are independent and IF the samples are representative (and for simulators, IF you know the distributions of the variables) and IF you use proper calculations THEN you may obtain some very useful data. But if any of the above conditions are not true then you may get garbage. Having to fulfill these conditions is why so many of us avoid statistical methods, or misuse them when we do attempt to use them.

The Design Master approach is different. Design Master works from the outside in, rather than the inside out. Let me explain.

With a statistical approach, such as Monte Carlo, one is trying to infer the boundaries of performance from representative samples. This is a hazardous method for assuring design reliability, since one never knows for sure whether or not the boundaries of performance have been identified. Also, for most practical cases, the degree of reliability required for a design requires one heck of a lot of Monte Carlo trials, which provide a "confidence" level, not a certainty.