This article briefly introduces the MATLAB â„¢ 1 data processing software, which is used to enhance the amount of program code when the storage capacity of the logic analyzer is limited. Most engineers will face the problem of memory limitation when using the large logic analyzer (LA) HP16500C equipment equipped with HP16517A high-speed status card to collect ultra-high-speed data (data rate higher than 135MHz).
The standard configuration of HP equipment usually provides a maximum memory capacity of 64k, and each test can only store 65536 data points. In order to accurately describe the characteristics of INL / DNL, ​​the data points that can be captured by 64k memory are far from meeting the demand. In fact, for INL and DNL test charts, the logic analyzer needs to collect 256k to 4M data points and provide them to MATLAB or other signal processing software for analysis.
When using the storage capacity of the above 64k standard data collection system, in order to accurately describe the characteristics of INL / DNL, ​​multiple sets of data records must be collected and merged into one file. For example, when 256k data points are needed, four sets of 64k data are collected. Before using MATLAB software (or similar software) introduced by the application note: Histogram TesTIng Determines DNL and INL Errors for data analysis, they need to be merged into together.
The following steps can be used to merge multiple data records into a sufficiently large INL / DNL file for INL / DNL data processing:
Collect 64k data points with a high-speed status card (HP16517A). Delete all the code specified by LA in the program file that does not belong to the program, and save the file. A specifies a new variable for the file content.MATLAB command: a = load ('inltest1'); collect another set of 64k data records with high-speed status card. Once again, delete all the code specified by LA in the program file that does not belong to the program, and save the file. Specify another new variable for the new data file content.
MATLAB command: b = load ('inltest2'); merge two sets of data records (A and B) and assign them a new variable.
MATLAB command: c = vertcat (a, b); If you need to detect the number of merged data records, you can enter size (c); in MATLAB, and then you should get 132k data records. Save this new set of data records as a .TXT or .DAT file so that MATLAB can process the data when calculating INL / DNL.
MATLAB command: save inldata.txt c -ascii; The above command saves the file in ASCII file format and stores it in a predefined directory. The INL / DNL test program can obtain these data as needed. If all steps are completed in one MATLAB session, the above process is performed. You can also execute pre-merged files in a loop. In this case, simply load the file that stores the data and specify a new variable.
MATLAB command: d = load ('inldata.txt'); Once this work is completed, a new set of data can be extracted and added to the existing data. Just collect another set of 64k data records and specify another matrix variable for its content.
MATLAB command: e = load ('inltest3'); merge the old text file (the current variable is d) and specify the new data variable as e.
MATLAB command: f = vertcat (d, e); Save the new and expanded data matrix to an ASCII file according to step 9. You can also use the commands in MATLAB: y = vertcat (a, b, c, d, e, f, g, h) to merge multiple variables at once, in short, you can use a variety of methods, procedures and configuration methods, using existing Equipment and simple software instructions complete these tests. The process provided here is just a simple MATLAB application example.
In order to construct the INL / DNL test program, simply call the INL / DNL test subroutine in MATLAB. Run the program and load continuous data sets into the program when requested. If you save the merged data in a .TXT or .DAT file, you must pay attention to the data path of the recording matrix file. When the program prompts, you must provide the exact path and file name for loading data into the test subroutine. The program also requires the number of data points (the size of the data matrix), the conversion result and its intermediate code. Before running the INL / DNL test procedure, you must confirm that you have this information.
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