Signal and Information Processing

ISSN: 2630-4805 (Online)

Journal Abbreviation: Signal Inf Process

Publication Frequency: Yearly

Article Processing Charges (APC): Click here for more details

Publishing Model: Open Access

Journal no: 78P

About the Journal

Signal and Information Processing is an international open access journal that publishes original research articles and reviews related to all fields related to signal and information processing. The journal includes digital signal processing, filtering and signal processing, compressed signal processing, artificial intelligence, neural networks, hardware implementation, data filtering and processing, human-computer interaction, signal processing applications, data fusion and remote sensing.



News: Pentagon’s artificial intelligence programs get huge boost in defense budget


This story was produced by Sludge, an investigative journalism website covering money in politics.

On Monday, President Trump signed the the $717 billion annual National Defense Authorization Act, which was easily passed by Congress in weeks prior. Much attention has understandably been placed on big-ticket items like $7.6 billion for acquiring 77 F-35 fighters, $21.9 billion for the nuclear weapons program, and $1.56 billion for three littoral combat ships—despite the fact that the Navy requested only one in the budget.

Posted: 2018-09-11

News: Facebook, NYU team up to make MRI scans faster through AI


Facebook is working with the NYU School of Medicine to shorten the length of time patients must spend in MRI scanners.

Facebook's Artificial Intelligence Research (FAIR) group and the medical school's radiology department are investigating whether artificial intelligence can make magnetic resonance imaging scans up to 10 times faster.

Such a development would not only reduce patient discomfort – scans can last 15 minutes to an hour – but also free up MRIs for more patients. "If this effort is successful, it will make MRI technology available to more people, expanding access to this key diagnostic tool," the research team says in a blog post on the Facebook website.

Posted: 2018-09-11
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Vol 1, No 1 (Published)


Table of Contents


by Lina Sun
292 Views, 11586 PDF Downloads

Fourier transform is a special integral transformation. The Fourier transform transforms the signal from the time domain to the frequency domain, and
the frequency domain method has many outstanding advantages compared with the classical time domain method. Although Fourier analysis is not the only
transform domain method in the field of information science and technology, it has to be recognized that Fourier transform analysis has always been widely used in
this field. Fourier transform is used to realize the filtering, modulation and sampling of the signal, which is the most important application of Fourier transform in
signal processing. Through the modulation of the signal can be low-frequency components of the signal modulation to high frequency, to achieve the spectrum shift,
to reduce inter-code crosstalk, improve the new noise resistance, is conducive to long-distance transmission of the signal. In addition, the signal sampling can be
continuous signal discretization, help to use the computer to deal with the signal. In short, Fourier transform has a very important role in signal processing, learning
Fourier transform is the basis for learning other frequency domain transformations.


by Zhimin Gong
238 Views, 3147 PDF Downloads

FM is widely used in communication systems. FM is widely used in high-fidelity music broadcasting, television audio signal transmission, satellite
communications and cellular telephone systems. The design is mainly use MATLAB integrated environment M files to prepare the formula in order to achieve FM
modulation and demodulation process. Then, it will draw out of the baseband signal, carrier signal and modulated time domain waveform signal. After that, it will
draw out the superimposed signal with noise signal separately, the coherent demodulated signal and the time domain waveform of the demodulated baseband signal.
Finally, the relationship between the bit error rate and the signal-to-noise ratio after the FM baseband signal is passed through the channel and the modulation and
demodulation system will be drawn out. Then, waveform will be compared through theoretical results to analyze the correctness of the simulation modulation and
demodulation system and the impact of noise on signal demodulation. In this design, the system development platform is Windows Vista while the tools used is
MATLAB 7.0. The program was running on the platform to complete the observation of FM modulation and demodulation as well as the demodulation of the
superimposed noise. The FM signal through the noise channel, modulation and demodulation system simulation purposes was achieved through this design.


by Weidong Li
260 Views, 666 PDF Downloads

Speech signal processing is an emerging discipline to study the processing of speech signals with digital signal processing technology and phonological
knowledge. It is one of the core technologies in the field of information science research. Passing information through voice is the most important, most effective,
most commonly used and convenient exchange form of information. The Matlab language is a very powerful computer application software for data analysis and
processing. It can transform sound files into discrete data files and then use their powerful matrix computing power to process data such as digital filtering, Fourier
transform, domain and frequency domain analysis, sound playback and a variety of graphics. Its signal processing and analysis toolbox for the voice signal analysis
provides a very rich function, the use of these functions can quickly and easily complete the voice signal processing and analysis, as well as signal visualization,
making human-computer interaction more convenient. Signal processing is one of the important applications of Matlab. This design is aimed at most of the voice
processing software content, operation inconvenience and other issues. The use of MATLAB 7.0 integrated GUI interface design, a variety of function calls to
achieve the voice signal frequency, amplitude, fourier transform and filtering, concise interface, easy to operate. All these have certain practical significance. Finally,
this paper puts forward his own views on the further development of speech signal processing.


by Zhanyi Lu
226 Views, 141 PDF Downloads

In recent years, with the rapid development of the economy, people rely more and more on mobile communication, and therefore greatly promoted the
rapid development of modern mobile communications industry, efficient mobile communication system has gradually become a new generation the direction of
development. This article describes the content of OFDM simulation and in mobile communications applications. This paper analyzes the principle of OFDM
technology, establishes the simulation model of mobile communication system, writes the program code of the system, establishes the simulation model, analyzes
the interference factors in the process of the mobile communication transmission, and completes the analysis of the simulation result through simulation. This paper
also focuses on the realization of orthogonal frequency division multiplexing (OFDM) and the performance of sub-channels and other parameters and reduces the
peak-to-average power ratio of OFDM systems. Finally, the application status and prospect of OFDM technology in the modern communication system are


by Dongxu Cheng
252 Views, 290 PDF Downloads

Mechanical signal processing is done by transforming some of the measurement signals, weakening the unwanted redundant signals in the mechanical
signal, filtering out the mixed noise interference, or turning the signal into a form that is easy to identify in order to extract its eigenvalues. The In this paper, the
time-frequency domain processing method of a mechanical signal is introduced. The simulated noisy period signal is constructed by Matlab, and the time-frequency
domain is processed. The signal filtering, correlation analysis, power spectrum analysis, and other methods of the characteristics and advantages.
Key words: Mechanical signal; noice interference; time-frequency domain processing