Digital Signal Processing

The Excel file contains samples of a laboratory-generated noisy voltage signal with a dc component under nonideal sampling.

This test signal is generated in a laboratory for assessing power frequency estimation algorithms.

The first column represents the sample time.

The second column represents the voltage signal samples.

The reference fundamental frequency is 46 Hz.

The nominal voltage amplitude is 10 V.

The actual sampling rate varies in the range of 9.99834~10.01027 kHz.



This paper is a novel digital signal processing software of the advanced conversion of text-to-speech synthesis technology, which has been available as a range of hardware products for more than ten years, to software. It was initially created as a replacement for character cell terminals and telephony applications, but it is now also used to give people who are visually impaired access to information. With a digital formant synthesizer used to mimic the human vocal tract, text-to-speech quality is very high in both understandability and naturalness.


The task of algorithm implementation in several applications of signal processing is the most interesting task for the engineers of the Digital Signal Processing field. The pressure most engineers have and looking for is how to solve these algorithms with less time and pain. This paper implements a technique and tools created to use with the microprocessor TMS 320 from Texas Instrument as a part of the Digital Signal Processing family which is helpful and expedited for such development.


The objective of this dataset is the fault diagnosis in diesel engines to assist the predictive maintenance, through the analysis of the variation of the pressure curves inside the cylinders and the torsional vibration response of the crankshaft. Hence a fault simulation model based on a zero-dimensional thermodynamic model was developed. The adopted feature vectors were chosen from the thermodynamic model and obtained from processing signals as pressure and temperature inside the cylinder, as well as, torsional vibration of the engine’s flywheel.


This real-life current signal was acquired from a wind generator.

The nominal fundamental frequency of the system is 60 Hz.

The sampling rate is 7.680 kHz, which corresponds to 128 samples per fundamental cycle.

The magnitude is given in amperes (A). The length of the signal is approximately one hour (3640 s).


Design of novel RF front-end hardware architectures and their associated measurement algorithms.
Research objectives, includes:
RO1: Novel architecture based upon Adaptive Wavelet Band-pass Sampling (AWBS) of RF Analog-to-Information Conversion (AIC).
RO2: Integration of AWBS for increasing the wideband sensing capabilities of real-time spectrum analyzers by using AICs.
RO3: Propose online calibration methods and algorithms for front-end hardware non-idealities compensation.