Abstract: In this paper, a new encoding algorithm of spectral envelope based on NLMS in G.729.1 for VoIP is proposed. In the TDAC part of G.729.1, the spectral envelope and MDCT coefficients extracted in the weighted CELP coding error (lower-band) and the higher-band input signal are encoded. In order to reduce allocation bits for spectral envelope coding, a new quantization algorithm based on NLMS is proposed. Also, reduced bits are used to enhance sound quality. The performance of the proposed algorithm is evaluated by sound quality and bit reduction rates in clean and frame loss conditions.
Abstract: In this paper a bank of velocity filters is devised to be
used for isolating a moving object with specific velocity in a sequence of frames. The approach used is a 3-D FFT based experimental procedure without applying any theoretical concept
from velocity filters. Accordingly, velocity filters are built using the
spectral signature of each separate moving object. Experimentation
reveals the capabilities of the constructed filter bank to separate moving objects as far as the amplitude as well as the direction of the
velocity are concerned.
Abstract: Multi-user interference (MUI) is the main reason of system deterioration in the Spectral Amplitude Coding Optical Code Division Multiple Access (SAC-OCDMA) system. MUI increases with the number of simultaneous users, resulting into higher probability bit rate and limits the maximum number of simultaneous users. On the other hand, Phase induced intensity noise (PIIN) problem which is originated from spontaneous emission of broad band source from MUI severely limits the system performance should be addressed as well. Since the MUI is caused by the interference of simultaneous users, reducing the MUI value as small as possible is desirable. In this paper, an extensive study for the system performance specified by MUI and PIIN reducing is examined. Vectors Combinatorial (VC) codes families are adopted as a signature sequence for the performance analysis and a comparison with reported codes is performed. The results show that, when the received power increases, the PIIN noise for all the codes increases linearly. The results also show that the effect of PIIN can be minimized by increasing the code weight leads to preserve adequate signal to noise ratio over bit error probability. A comparison study between the proposed code and the existing codes such as Modified frequency hopping (MFH), Modified Quadratic- Congruence (MQC) has been carried out.
Abstract: A new code for spectral-amplitude coding optical
code-division multiple-access system is proposed called Random
diagonal (RD) code. This code is constructed using code segment and
data segment. One of the important properties of this code is that the
cross correlation at data segment is always zero, which means that
Phase Intensity Induced Noise (PIIN) is reduced. For the performance
analysis, the effects of phase-induced intensity noise, shot noise, and
thermal noise are considered simultaneously. Bit-error rate (BER)
performance is compared with Hadamard and Modified Frequency
Hopping (MFH) codes. It is shown that the system using this new
code matrices not only suppress PIIN, but also allows larger number
of active users compare with other codes. Simulation results shown
that using point to point transmission with three encoded channels,
RD code has better BER performance than other codes, also its found
that at 0 dbm PIIN noise are 10-10 and 10-11 for RD and MFH
respectively.
Abstract: In order to develop forest management strategies in
tropical forest in Malaysia, surveying the forest resources and
monitoring the forest area affected by logging activities is essential.
There are tremendous effort has been done in classification of land
cover related to forest resource management in this country as it is a
priority in all aspects of forest mapping using remote sensing and
related technology such as GIS. In fact classification process is a
compulsory step in any remote sensing research. Therefore, the main
objective of this paper is to assess classification accuracy of
classified forest map on Landsat TM data from difference number of
reference data (200 and 388 reference data). This comparison was
made through observation (200 reference data), and interpretation
and observation approaches (388 reference data). Five land cover
classes namely primary forest, logged over forest, water bodies, bare
land and agricultural crop/mixed horticultural can be identified by
the differences in spectral wavelength. Result showed that an overall
accuracy from 200 reference data was 83.5 % (kappa value
0.7502459; kappa variance 0.002871), which was considered
acceptable or good for optical data. However, when 200 reference
data was increased to 388 in the confusion matrix, the accuracy
slightly improved from 83.5% to 89.17%, with Kappa statistic
increased from 0.7502459 to 0.8026135, respectively. The accuracy
in this classification suggested that this strategy for the selection of
training area, interpretation approaches and number of reference data
used were importance to perform better classification result.
Abstract: Vector quantization is a powerful tool for speech
coding applications. This paper deals with LPC Coding of speech
signals which uses a new technique called Multi Switched Split
Vector Quantization (MSSVQ), which is a hybrid of Multi, switched,
split vector quantization techniques. The spectral distortion
performance, computational complexity, and memory requirements
of MSSVQ are compared to split vector quantization (SVQ), multi
stage vector quantization(MSVQ) and switched split vector
quantization (SSVQ) techniques. It has been proved from results that
MSSVQ has better spectral distortion performance, lower
computational complexity and lower memory requirements when
compared to all the above mentioned product code vector
quantization techniques. Computational complexity is measured in
floating point operations (flops), and memory requirements is
measured in (floats).
Abstract: Heart-s electric field can be measured anywhere on
the surface of the body (ECG). When individuals touch, one person-s
ECG signal can be registered in other person-s EEG and elsewhere
on his body. Now, the aim of this study was to test the hypothesis
that physical contact (hand-holding) of two persons changes their
heart rate variability. Subjects were sixteen healthy female (age: 20-
26) which divided into eight sets. In each sets, we had two friends
that they passed intimacy test of J.sternberg. ECG of two subjects
(each set) acquired for 5 minutes before hand-holding (as control
group) and 5 minutes during they held their hands (as experimental
group). Then heart rate variability signals were extracted from
subjects' ECG and analyzed in linear feature space (time and
frequency domain) and nonlinear feature space. Considering the
results, we conclude that physical contact (hand-holding of two
friends) increases parasympathetic activity, as indicate by increase
SD1, SD1/SD2, HF and MF power (p
Abstract: In this article a modification of the algorithm of the fuzzy ART network, aiming at returning it supervised is carried out. It consists of the search for the comparison, training and vigilance parameters giving the minimum quadratic distances between the output of the training base and those obtained by the network. The same process is applied for the determination of the parameters of the fuzzy ARTMAP giving the most powerful network. The modification consist in making learn the fuzzy ARTMAP a base of examples not only once as it is of use, but as many time as its architecture is in evolution or than the objective error is not reached . In this way, we don-t worry about the values to impose on the eight (08) parameters of the network. To evaluate each one of these three networks modified, a comparison of their performances is carried out. As application we carried out a classification of the image of Algiers-s bay taken by SPOT XS. We use as criterion of evaluation the training duration, the mean square error (MSE) in step control and the rate of good classification per class. The results of this study presented as curves, tables and images show that modified fuzzy ARTMAP presents the best compromise quality/computing time.
Abstract: Music has a great effect on human body and mind; it
can have a positive effect on hormone system. Objective of this study
is to analysis the effect of music (carnatic, hard rock and jazz) on
brain activity during mental work load using electroencephalography
(EEG). Eight healthy subjects without special musical education
participated in the study. EEG signals were acquired at frontal (Fz),
parietal (Pz) and central (Cz) lobes of brain while listening to music
at three experimental condition (rest, music without mental task and
music with mental task). Spectral powers features were extracted at
alpha, theta and beta brain rhythms. While listening to jazz music, the
alpha and theta powers were significantly (p < 0.05) high for rest as
compared to music with and without mental task in Cz. While
listening to Carnatic music, the beta power was significantly (p <
0.05) high for with mental task as compared to rest and music
without mental task at Cz and Fz location. This finding corroborates
that attention based activities are enhanced while listening to jazz and
carnatic as compare to Hard rock during mental task.
Abstract: In the paper, the relative performances on spectral
classification of short exon and intron sequences of the human and
eleven model organisms is studied. In the simulations, all
combinations of sixteen one-sequence numerical representations, four
threshold values, and four window lengths are considered. Sequences
of 150-base length are chosen and for each organism, a total of
16,000 sequences are used for training and testing. Results indicate
that an appropriate combination of one-sequence numerical
representation, threshold value, and window length is essential for
arriving at top spectral classification results. For fixed-length
sequences, the precisions on exon and intron classification obtained
for different organisms are not the same because of their genomic
differences. In general, precision increases as sequence length
increases.
Abstract: In single trial analysis, when using Principal
Component Analysis (PCA) to extract Visual Evoked Potential
(VEP) signals, the selection of principal components (PCs) is an
important issue. We propose a new method here that selects only
the appropriate PCs. We denote the method as selective eigen-rate
(SER). In the method, the VEP is reconstructed based on the rate
of the eigen-values of the PCs. When this technique is applied on
emulated VEP signals added with background
electroencephalogram (EEG), with a focus on extracting the
evoked P3 parameter, it is found to be feasible. The improvement
in signal to noise ratio (SNR) is superior to two other existing
methods of PC selection: Kaiser (KSR) and Residual Power (RP).
Though another PC selection method, Spectral Power Ratio (SPR)
gives a comparable SNR with high noise factors (i.e. EEGs), SER
give more impressive results in such cases. Next, we applied SER
method to real VEP signals to analyse the P3 responses for
matched and non-matched stimuli. The P3 parameters extracted
through our proposed SER method showed higher P3 response for
matched stimulus, which confirms to the existing neuroscience
knowledge. Single trial PCA using KSR and RP methods failed to
indicate any difference for the stimuli.
Abstract: An end-member selection method for spectral unmixing that is based on Particle Swarm Optimization (PSO) is developed in this paper. The algorithm uses the K-means clustering algorithm and a method of dynamic selection of end-members subsets to find the appropriate set of end-members for a given set of multispectral images. The proposed algorithm has been successfully applied to test image sets from various platforms such as LANDSAT 5 MSS and NOAA's AVHRR. The experimental results of the proposed algorithm are encouraging. The influence of different values of the algorithm control parameters on performance is studied. Furthermore, the performance of different versions of PSO is also investigated.
Abstract: The purpose of this study was to analyze the correlation
between permitted building areas and housing distribution ratios and
their fluctuation, and test a distribution model during 3 successive governments in 5 cities including Bucheon in reference to the time
series administrative data, and thereby, interpret the results of the analysis in association with the policies pursued by the successive
governments to examine the structural fluctuation of permitted building areas and housing distribution ratios.
In order to analyze the fluctuation of permitted building areas and
housing distribution ratios during 3 successive governments and
examine the cycles of the time series data, the spectral analysis was performed, and in order to analyze the correlation between permitted
building areas and housing distribution ratios, the tabulation was performed to describe the correlations statistically, and in order to
explain about differences of fluctuation distribution of permitted building areas and housing distribution ratios among 3 governments,
the goodness of fit test was conducted.
Abstract: The RR interval series is non-stationary and unevenly
spaced in time. For estimating its power spectral density (PSD) using
traditional techniques like FFT, require resampling at uniform
intervals. The researchers have used different interpolation
techniques as resampling methods. All these resampling methods
introduce the low pass filtering effect in the power spectrum. The
lomb transform is a means of obtaining PSD estimates directly from
irregularly sampled RR interval series, thus avoiding resampling. In
this work, the superiority of Lomb transform method has been
established over FFT based approach, after applying linear and
cubicspline interpolation as resampling methods, in terms of
reproduction of exact frequency locations as well as the relative
magnitudes of each spectral component.
Abstract: One important objective in Precision Agriculture is to minimize the volume of herbicides that are applied to the fields through the use of site-specific weed management systems. In order to reach this goal, two major factors need to be considered: 1) the similar spectral signature, shape and texture between weeds and crops; 2) the irregular distribution of the weeds within the crop's field. This paper outlines an automatic computer vision system for the detection and differential spraying of Avena sterilis, a noxious weed growing in cereal crops. The proposed system involves two processes: image segmentation and decision making. Image segmentation combines basic suitable image processing techniques in order to extract cells from the image as the low level units. Each cell is described by two area-based attributes measuring the relations among the crops and the weeds. From these attributes, a hybrid decision making approach determines if a cell must be or not sprayed. The hybrid approach uses the Support Vector Machines and the Fuzzy k-Means methods, combined through the fuzzy aggregation theory. This makes the main finding of this paper. The method performance is compared against other available strategies.
Abstract: In 1990 [1] the subband-DFT (SB-DFT) technique was proposed. This technique used the Hadamard filters in the decomposition step to split the input sequence into low- and highpass sequences. In the next step, either two DFTs are needed on both bands to compute the full-band DFT or one DFT on one of the two bands to compute an approximate DFT. A combination network with correction factors was to be applied after the DFTs. Another approach was proposed in 1997 [2] for using a special discrete wavelet transform (DWT) to compute the discrete Fourier transform (DFT). In the first step of the algorithm, the input sequence is decomposed in a similar manner to the SB-DFT into two sequences using wavelet decomposition with Haar filters. The second step is to perform DFTs on both bands to obtain the full-band DFT or to obtain a fast approximate DFT by implementing pruning at both input and output sides. In this paper, the wavelet-based DFT (W-DFT) with Haar filters is interpreted as SB-DFT with Hadamard filters. The only difference is in a constant factor in the combination network. This result is very important to complete the analysis of the W-DFT, since all the results concerning the accuracy and approximation errors in the SB-DFT are applicable. An application example in spectral analysis is given for both SB-DFT and W-DFT (with different filters). The adaptive capability of the SB-DFT is included in the W-DFT algorithm to select the band of most energy as the band to be computed. Finally, the W-DFT is extended to the two-dimensional case. An application in image transformation is given using two different types of wavelet filters.
Abstract: In this paper, we first give the representation of the general solution of the following inverse eigenvalue problem (IEP): Given X ∈ Rn×p and a diagonal matrix Λ ∈ Rp×p, find nontrivial real-valued symmetric arrow-head matrices A and B such that AXΛ = BX. We then consider an optimal approximation problem: Given real-valued symmetric arrow-head matrices A, ˜ B˜ ∈ Rn×n, find (A, ˆ Bˆ) ∈ SE such that Aˆ − A˜2 + Bˆ − B˜2 = min(A,B)∈SE (A−A˜2 +B −B˜2), where SE is the solution set of IEP. We show that the optimal approximation solution (A, ˆ Bˆ) is unique and derive an explicit formula for it.
Abstract: Multi-level voltage source inverters offer several
advantages such as; derivation of a refined output voltage with
reduced total harmonic distortion (THD), reduction of voltage ratings
of the power semiconductor switching devices and also the reduced
electro-magnetic-interference problems etc. In this paper, new
carrier-overlapped phase-disposition or sub-harmonic sinusoidal
pulse width modulation (CO-PD-SPWM) and also the carrieroverlapped
phase-disposition space vector modulation (CO-PDSVPWM)
schemes for a six-level diode-clamped inverter topology
are proposed. The principle of the proposed PWM schemes is similar
to the conventional PD-PWM with a little deviation from it in the
sense that the triangular carriers are all overlapped. The overlapping
of the triangular carriers on one hand results in an increased number
of switchings, on the other hand this facilitates an improved spectral
performance of the output voltage. It is demonstrated through
simulation studies that the six-level diode-clamped inverter with the
use of CO-PD-SPWM and CO-PD-SVPWM proposed in this paper is
capable of generating multiple levels in its output voltage. The
advantages of the proposed PWM schemes can be derived to benefit,
especially at lower modulation indices of the inverter and hence this
aspect of the proposed PWM schemes can be well exploited in high
power applications requiring low speeds of operation of the drive.
Abstract: The dynamic spectrum allocation solutions such as
cognitive radio networks have been proposed as a key technology to
exploit the frequency segments that are spectrally underutilized.
Cognitive radio users work as secondary users who need to
constantly and rapidly sense the presence of primary users or
licensees to utilize their frequency bands if they are inactive. Short
sensing cycles should be run by the secondary users to achieve
higher throughput rates as well as to provide low level of interference
to the primary users by immediately vacating their channels once
they have been detected. In this paper, the throughput-sensing time
relationship in local and cooperative spectrum sensing has been
investigated under two distinct scenarios, namely, constant primary
user protection (CPUP) and constant secondary user spectrum
usability (CSUSU) scenarios. The simulation results show that the
design of sensing slot duration is very critical and depends on the
number of cooperating users under CPUP scenario whereas under
CSUSU, cooperating more users has no effect if the sensing time
used exceeds 5% of the total frame duration.
Abstract: A generalized method for small-signal simulation of
avalanche noise in Mixed Tunneling Avalanche Transit Time
(MITATT) device is presented in this paper where the effect of series
resistance is taken into account. The method is applied to a
millimeter-wave Double Drift Region (DDR) MITATT device based
on Silicon to obtain noise spectral density and noise measure as a
function of frequency for different values of series resistance. It is
found that noise measure of the device at the operating frequency
(122 GHz) with input power density of 1010 Watt/m2 is about 35 dB
for hypothetical parasitic series resistance of zero ohm (estimated
junction temperature = 500 K). Results show that the noise measure
increases as the value of parasitic resistance increases.