We study the global topology of the syntactic and semantic distributional similarity networks for English through the technique of spectral analysis. We observe that while the syntactic network has a hierarchical structure with strong communities and their mixtures, the semantic network has several tightly knit communities along with a large core without any such welldeﬁned community structure. intriguing question, whereby we construct the syntactic and semantic distributional similarity network (DSN) and analyze their spectrum to understand their global topology. ...
Recent research has shown that language and the socio-cognitive phenomena associated with it can be aptly modeled and visualized through networks of linguistic entities. However, most of the existing works on linguistic networks focus only on the local properties of the networks. This study is an attempt to analyze the structure of languages via a purely structural technique, namely spectral analysis, which is ideally suited for discovering the global correlations in a network.
Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Short Exon Detection in DNA Sequences Based on Multifeature Spectral Analysis
Technical Analysts often find a system or technical method that seems
extremely profitable and convenient to follow - one that they think has been
overlooked by the professionals. Sometimes they are right, but most often that
method doesn't work in practical trading or for a longer time.
Technical analysis uses price and related data to decide when to buy and sell.
The methods used can be interpretive as chart patterns and astrology, or as
specific as mathematical formulas and spectral analysis. All factors that
influence the markets are assumed to be netted out as the current price....
Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Localized Spectral Analysis of Fluctuating Power Generation from Solar Energy Systems
This thesis aimed to apply the SEM for dynamic analysis of cracked beam subjected moving harmonic force in the frequency domain. Namely, the frequency response of a cracked beam subjected to moving harmonic force is obtained explicitly and examined in dependence upon the load and crack parameters. This task is acknowledged herein spectral analysis of cracked beam subjected to moving load.
As we sit at the microscope with users, waiting for data to collect, we frequently find
ourselves answering the same questions, time after time. The users need to know what
their data tells them about the sample, how it should be interpreted or processed, or a
myriad of other details about the experiment. At other times, we find ourselves
explaining why a particular experiment cannot be performed, or, at least, why it is more
complex than appears at first glance. Sometimes students need help describing these
issues to their advisors.
The inﬁnite-dimensional unitary group U(∞) is the inductive limit of growing compact unitary groups U(N ). In this paper we solve a problem of harmonic analysis on U(∞) stated in [Ol3]. The problem consists in computing spectral decomposition for a remarkable 4-parameter family of characters of U(∞). These characters generate representations which should be viewed as analogs of nonexisting regular representation of U(∞).
Two decades ago when we wrote Spectral Methods in Fluid Dynamics (1988),
the subject was still fairly novel. Motivated by the many favorable comments
we have received and the continuing interest in that book (which will be
referred to as CHQZ1), and yet desiring to present a more modern perspective,
we embarked on the project which resulted in our recent book (Canuto
et al. (2006), referred to as CHQZ2) and the present new book (referred to
Frequency analysis of digital signals and systems was discussed in Chapter 4. To perform frequency analysis on a discrete-time signal, we converted the time-domain sequence into the frequency-domain representation using the z-transform, the discrete-time Fourier transform (DTFT), or the discrete Fourier transform (DFT). The widespread application of the DFT to spectral analysis, fast convolution, and data transmission is due to the development of the fast Fourier transform (FFT) algorithm for its computation....
The final chapter of the book presents an innovative method for fluid mechanical
design in which an object within the flow field is build element-by-element. Each
element is introduced into the flow, and its effect on a cost function is minimized with
respect to the object’s position. An element may represent added material or a
removed part of the existing structure. This chapter presents a strong degree of
The Signal Processing Toolbox is a collection of tools built on the MATLAB®
numeric computing environment. The toolbox supports a wide range of signal
processing operations, from waveform generation to filter design and
implementation, parametric modeling, and spectral analysis. The toolbox
provides two categories of tools:
Fast Fourier Transform and Its Applications
Frequency analysis of digital signals and systems was discussed in Chapter 4. To perform frequency analysis on a discrete-time signal, we converted the time-domain sequence into the frequency-domain representation using the z-transform, the discrete-time Fourier transform (DTFT), or the discrete Fourier transform (DFT). The widespread application of the DFT to spectral analysis, fast convolution, and data transmission is due to the development of the fast Fourier transform (FFT) algorithm for its computation.
LINEAR PREDICTION MODELS
Linear Prediction Coding Forward, Backward and Lattice Predictors Short-term and Long-Term Linear Predictors MAP Estimation of Predictor Coefficients Sub-Band Linear Prediction Signal Restoration Using Linear Prediction Models Summary
inear prediction modelling is used in a diverse area of applications, such as data forecasting, speech coding, video coding, speech recognition, model-based spectral analysis, model-based interpolation, signal restoration, and impulse/step event detection.
The past 20 years witnessed an expansion of power spectrum estimation techniques, which have
proved essential in many applications, such as communications, sonar, radar, speech/image processing,
geophysics, and biomedical signal processing [13, 11, 7].
Transfer Functions and Spectral Models Hệ thống đại diện hệ thống là một tập hợp có tổ chức của các thành phần, các khái niệm có vai trò là để thực hiện một hoặc nhiều tác vụ. Các quan điểm được thông qua trong các đặc tính của hệ thống là chỉ để đối phó với các mối quan hệ đầu vào-đầu ra, với nguyên nhân và tác động của chúng, không phân biệt về bản chất vật lý của các hiện tượng liên quan.
The Spectrum of Periodic Signals
Signals dwell both in the time and frequency domains; we can equally accurately think of them as values changing in time (time domain), or as blendings of fundamental frequencies (spectral domain). The method for determining these fundamental frequencies from the time variations is called Fourier or spectral analysis. Similar techniques allow returning to the time domain representation from the frequency domain description.