Fred C Scweppe - Collected Quotes

 "A bias can be considered a limiting case of a nonwhite disturbance as a constant is the most time-correlated process possible." (Fred C Scweppe, "Uncertain dynamic systems", 1973)

"Changes of variables can be helpful for iterative and parametric solutions even if they do not linearize the problem. For example, a change of variables may change the 'shape' of J(x) into a more suitable form. Unfortunately there seems to be no· general way to choose the 'right' change of variables. Success depends on the particular problem and the engineer's insight. However, the possibility of a change of variables should always be considered."(Fred C Scweppe, "Uncertain dynamic systems", 1973)

"Decision-making problems (hypothesis testing) involve situations where it is desired to make a choice among various alternative decisions (hypotheses). Such problems can be viewed as generalized state estimation problems where the definition of state has simply been expanded." (Fred C Scweppe, "Uncertain dynamic systems", 1973)

"Hypothesis testing can introduce the need for multiple models for the multiple hypotheses and,' if appropriate, a priori probabilities. The one modeling aspect of hypothesis testing that has no estimation counterpart is the problem of specifying the hypotheses to be considered. Often this is a critical step which influences both performance arid the difficulty of implementation." (Fred C Scweppe, "Uncertain dynamic systems", 1973)

"Modeling is definitely the most important and critical problem. If the mathematical model is not valid, any subsequent analysis, estimation, or control study is meaningless. The development of the model in a convenient form can greatly reduce the complexity of the actual studies." (Fred C Scweppe, "Uncertain dynamic systems", 1973)

"Pattern recognition can be viewed as a special case of hypothesis testing. In pattern recognition, an observation z is to be used to decide what pattern caused it. Each possible pattern can be viewed as one hypothesis. The main problem in pattern recognition is the development of models for the z corresponding to each pattern (hypothesis)." (Fred C Scweppe, "Uncertain dynamic systems", 1973)

"System theory is a tool which engineers use to help them design the 'best' system to do the job that must be done. A dominant characteristic of system theory is the interest in the analysis and design (synthesis) of systems from an input-output point of view. System theory uses mathematical manipulation of a mathematical model to help design the actual system." (Fred C Scweppe, "Uncertain dynamic systems", 1973)

"The biggest (and sometimes insurmountable) problem is usually to use the available data (information, measurements, etc.) to find out what the system is actually doing (i.e., to estimate its state). If the system's state can be estimated to some reasonable accuracy, the desired control is often obvious (or can be obtained by the use of deterministic control theory)." (Fred C Scweppe, "Uncertain dynamic systems", 1973)

"The choice of model is often the most critical aspect of a design and development engineering job, but it is impossible to give explicit rules or techniques." (Fred C Scweppe, "Uncertain dynamic systems", 1973)

"The power and beauty of stochastic approximation theory is that it provides simple, easy to implement gain sequences which guarantee convergence without depending (explicitly) on knowledge of the function to be minimized or the noise properties. Unfortunately, convergence is usually extremely slow. This is to be expected, as "good performance" cannot be expected if no (or very little) knowledge of the nature of the problem is built into the algorithm. In other words, the strength of stochastic approximation (simplicity, little a priori knowledge) is also its weakness." (Fred C Scweppe, "Uncertain dynamic systems", 1973)

"The pseudo approach to uncertainty modeling refers to the use of an uncertainty model instead of using a deterministic model which is actually (or at least theoretically) available. The uncertainty model may be desired because it results in a simpler analysis, because it is too difficult (expensive) to gather all the data necessary for an exact model, or because the exact model is too complex to be included in the computer." (Fred C Scweppe, "Uncertain dynamic systems", 1973)

"[A] system is represented by a mathematical model which may take many forms, such as algebraic equations, finite state machines, difference equations, ordinary differential equations, partial differential equations, and functional equations. The system model may be uncertain, as the mathematical model may not be known completely." (Fred C Scweppe, "Uncertain dynamic systems", 1973)

"The term hypothesis testing arises because the choice as to which process is observed is based on hypothesized models. Thus hypothesis testing could also be called model testing. Hypothesis testing is sometimes called decision theory. The detection theory of communication theory is a special case." (Fred C Scweppe, "Uncertain dynamic systems", 1973)