No abstract available

No abstract available

[en] To obtain maximum data from the observation results some decomposition problems of data interpretation are considered. Algorithms intended to solve the nonlinear problems of data interpretation are given. Considered is the problem of identification and comparison of two spectra with a different number of components in them, arising in the course of evaluation of the model to experiment correspondence. It is shown that the approaches considered to the solution of decomposition problems of interpretation stage permit to computerize total mathematical treatment of observation results including a stable solution of inverse problems characteristic of spectrometric experiments

[en] A new approach towards comparing two spectra based on preliminary identification of line positions is considered. It is implemented in a program, IDENT, written in FORTRAN, which checks setting of dispersions and prints out information on the nature of spectra coincidence

[en] Short communication

[en] Short note. 3 refs

[en] Many subjects in the domain of radiation are characterized by radiation fields with a continuous energy spectrum. By using actual spectrometers it is not possible to determine directly the energy spectrum of the measured field. This literature study has been intended to find out which methods have been employed up till now to calculate, starting from the measured spectrum, the original energy spectrum. The unraveling consists of two steps. First the data from the detection system have to be determined. This forms the necessary input for the second step, the actual unraveling. For both steps a survey has been made of used methods, together with the possible advantages and disadvantages. Finally a number of conclusions are formulated and application possibilities are indicated. (author). 117 refs.; 52 figs

[en] A linear resolution function in a physical measurement leads to data values and standard deviations at, say, N points. It is noted that the associated resolution functions may require that a number n of particular linear combinations of the data values be each not significantly different from zero. One is left with at most N-n parameters to evaluate. If the resolution functions are reasonably behaved, one can show that one sensible way to describe the underlying spectrum treats it as a linear combination of the given resolution functions and includes all the significant information from the data. An iterative search for the best component available to minimize the chi-square of the next fit to the data leads to a conjugate gradient technique. Programs based on the technique have been successfully used to obtain neutron spectra as a function of energy; in raw data from a pulse height analysis of proton recoils in a proportional counter, and where the raw data are time of flight spectra from a time dependent pulse of known form. It is planned to incorporate these, together with working programs respectively for photonuclear analysis and to explore the impurity concentration profile in a surface, into a single ''work-bench'' type program. A suitably difficult model unfolding problem has been developed and used to show the strengths and weaknesses of a number of other methods that have been used for unfolding

No abstract available

No abstract available