Abstract: In this paper we present a general formalism for the
establishment of the family of selective regressor affine projection
algorithms (SR-APA). The SR-APA, the SR regularized APA (SR-RAPA),
the SR partial rank algorithm (SR-PRA), the SR binormalized
data reusing least mean squares (SR-BNDR-LMS), and the SR normalized
LMS with orthogonal correction factors (SR-NLMS-OCF)
algorithms are established by this general formalism. We demonstrate
the performance of the presented algorithms through simulations in
acoustic echo cancellation scenario.
Abstract: Group-III nitride material as particularly AlxGa1-xN is
one of promising optoelectronic materials to require for shortwavelength
devices. To achieve the high-quality AlxGa1-xN films for
a high performance of such devices, AlN-nucleation layers are the
important factor. To improve the AlN-nucleation layers with a
variation of Ga-addition, XRD measurements were conducted to
analyze the crystalline quality of the subsequent Al0.1Ga0.9N with the
minimum ω-FWHMs of (0002) and (10-10) reflections of 425 arcsec
and 750 arcsec, respectively. SEM and AFM measurements were
performed to observe the surface morphology and TEM
measurements to identify the microstructures and orientations.
Results showed that the optimized Ga-atoms in the Al(Ga)Nnucleation
layers improved the surface diffusion to form moreuniform
crystallites in structure and size, better alignment of each
crystallite, and better homogeneity of island distribution. This, hence,
improves the orientation of epilayers on the Si-surface and finally
improves the crystalline quality and reduces the residual strain of
subsequent Al0.1Ga0.9N layers.
Abstract: In turning hardened steel, polycrystalline cubic boron
nitride (cBN) compacts are widely used, due to their higher hardness
and higher thermal conductivity. However, in milling hardened steel,
fracture of cBN cutting tools readily occurs because they have poor
fracture toughness. Therefore, coated cemented carbide tools, which
have good fracture toughness and wear resistance, are generally
widely used. In this study, hardened steel (ASTM D2, JIS SKD11,
60HRC) was milled with three physical vapor deposition
(PVD)-coated cemented carbide end mill cutters in order to determine
effective tool materials for cutting hardened steel at high cutting
speeds. The coating films used were (Ti,W)N/(Ti,W,Si)N and
(Ti,W)N/(Ti,W,Si,Al)N coating films. (Ti,W,Si,Al)N is a new type of
coating film. The inner layer of the (Ti,W)N/(Ti,W,Si)N and
(Ti,W)N/(Ti,W,Si,Al)N coating system is (Ti,W)N coating film, and
the outer layer is (Ti,W,Si)N and (Ti,W,Si,Al)N coating films,
respectively. Furthermore, commercial (Ti,Al)N-based coating film
was also used. The following results were obtained: (1) In milling
hardened steel at a cutting speed of 3.33 m/s, the tool wear width of the
(Ti,W)N/(Ti,W,Si,Al)N-coated tool was smaller than that of the
(Ti,W)N/(Ti,W,Si)N-coated tool. And, compared with the commercial
(Ti,Al)N, the tool wear width of the (Ti,W)N/(Ti,W,Si,Al)N-coated
tool was smaller than that of the (Ti,Al)N-coated tool. (2) The tool
wear of the (Ti,W)N/(Ti,W,Si,Al)N-coated tool increased with an
increase in cutting speed. (3) The (Ti,W)N/(Ti,W,Si,Al)N-coated
cemented carbide was an effective tool material for high-speed cutting
below a cutting speed of 3.33 m/s.
Abstract: Speech corpus is one of the major components in a
Speech Processing System where one of the primary requirements
is to recognize an input sample. The quality and details captured
in speech corpus directly affects the precision of recognition. The
current work proposes a platform for speech corpus generation using
an adaptive LMS filter and LPC cepstrum, as a part of an ANN
based Speech Recognition System which is exclusively designed to
recognize isolated numerals of Assamese language- a major language
in the North Eastern part of India. The work focuses on designing an
optimal feature extraction block and a few ANN based cooperative
architectures so that the performance of the Speech Recognition
System can be improved.
Abstract: The least mean square (LMS) algorithmis one of the
most well-known algorithms for mobile communication systems
due to its implementation simplicity. However, the main limitation
is its relatively slow convergence rate. In this paper, a booster
using the concept of Markov chains is proposed to speed up the
convergence rate of LMS algorithms. The nature of Markov
chains makes it possible to exploit the past information in the
updating process. Moreover, since the transition matrix has a
smaller variance than that of the weight itself by the central limit
theorem, the weight transition matrix converges faster than the
weight itself. Accordingly, the proposed Markov-chain based
booster thus has the ability to track variations in signal
characteristics, and meanwhile, it can accelerate the rate of
convergence for LMS algorithms. Simulation results show that the
LMS algorithm can effectively increase the convergence rate and
meantime further approach the Wiener solution, if the
Markov-chain based booster is applied. The mean square error is
also remarkably reduced, while the convergence rate is improved.
Abstract: The morphological parameter of a thin film surface
can be characterized by power spectral density (PSD) functions
which provides a better description to the topography than the RMS
roughness and imparts several useful information of the surface
including fractal and superstructure contributions. Through the
present study Nanoparticle copper/carbon composite films were
prepared by co-deposition of RF-Sputtering and RF-PECVD method
from acetylene gas and copper target. Surface morphology of thin
films is characterized by using atomic force microscopy (AFM). The
Carbon content of our films was obtained by Rutherford Back
Scattering (RBS) and it varied from .4% to 78%. The power values of
power spectral density (PSD) for the AFM data were determined by
the fast Fourier transform (FFT) algorithms. We investigate the effect
of carbon on the roughness of thin films surface. Using such
information, roughness contributions of the surface have been
successfully extracted.