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This volume includes four (4) software distributions (MATLAB, IDL, Fortran, and DAQ). The MATLAB and DAQ Software Distributions were developed in collaboration with Advanced Technology Laboratories (ATL). To acquire the MATLAB Software Distribution, visit www.mathworks.com . To acquire the DAQ Software Distribution, visit www.idl.noaa.gov/daq .

MATLAB is a tool for technical computing, research, and development in science and engineering. Its language is a powerful tool for technical computing, data processing, visualization, and numerical solution of differential equations, optimization, finite element methods, statistics, signal and image processing, and data mining. MATLAB runs on a wide range of platforms, including Mac OS, Windows, and Linux. It has a large user base, a strong technical support infrastructure, and an active international developer community. For additional information about MATLAB, visit www.mathworks.com .

The software is designed to be run on a PC with Microsoft Windows 7 and can be installed on all versions of Windows operating systems, including Windows XP, Vista, Windows 7, Windows 8 and Windows 10.

The software consists of a set of MATLAB functions for image acquisition, image processing and visualization, and a set of Fortran 90 programs that can be compiled and linked to produce a standalone executable for data acquisition.

The user interface consists of an image file browser to allow selection of files for data acquisition and a text-based file-processing interface to allow data files to be converted to an image file and processed using a set of MATLAB functions.

The variability in the signal sum was determined to be 12.7%, a factor of almost 4 less than the variability in the integral. This variability is quite acceptable considering the simplicity and limited number of operations in the signal sum. This is in agreement with the findings of ScanImage [1], which reports a variability of 11.4% in their detector system.

We next evaluated the performance of our method of background rejection (Figure 2A). The voltage pulse at the input of the preamp was modeled as a Poisson process with mean photon rate of 2.5 photons per second and was centered at 0.0565 V. The amplifier response was modeled as a flat first-order low-pass filter with cutoff frequency at 6 Hz. The data was sampled at 20 kHz. Trials were repeated with Poisson-distributed pulses of different durations.

The functions in the Vimba toolbox have either a Type 1 or a Type 2 style interface, as described in the MATLAB help. The functions that can be used for every type of adapter are listed in Table 1. The functions that are specific to the adapter are listed in Table 2. The adapter-specific functions are described in the sample code provided with the documentation. 827ec27edc