摘要：We designed a universal digital energy spectroscopy based on online digital signal processing. A prototype system was built and tested. Signals from radiation detectors were processed via a digital filter whose coefficients could be modified without changing the hardware. The paper introduces the hardware design of the digital energy spectroscopy system as well as the full set of software consisting of the selection of the coefficients of the finite impulse response (fir) filter and the coding in the field-programmable gate array (FPGA). The system was tested with the high purity germanium (HPGe) detector. The results showed that this prototype can achieve an energy resolution close to that of a traditional multi-channel analyzer (MCA) with a much higher counting rate.

摘要：Frequency sampling is one of the popular methods in fir digital filter design. In the frequency sampling method the value of transition band samples, which are usually obtained by consulting a table, must be determined in order to make the attenuation within the stopband maximal. However, the value obtained by searching for table can not be ensured to be optimal. Evolutionary programming (EP), a multi agent stochastic optimization technique, can lead to global optimal solutions for complex problems. In this paper a new application of EP to frequency sampling method is introduced. Two examples of lowpass and bandpass fir filters are presented, and the steps of EP realization and experimental results are given. Experimental results show that the value of transition band samples obtained by EP can be ensured to be optimal and the performance of the filter is improved.