Improved conjugate gradient implementation for least squares support vector machines

As a promising method for pattern recognition and function estimation, least squares support vector machines (LS-SVM) express the training in terms of solving a linear system instead of a quadratic programming problem as for conventional support vector machines (SVM). In this paper, by using the information provided by the equality constraint, we transform the minimization problem with a single equality constraint in LS-SVM into an unconstrained minimization problem, then propose reduced formulations for LS-SVM. By introducing this transformation, the times of using conjugate gradient (CG) method, which is a greatly time-consuming step in obtaining the numerical solution, are reduced to one instead of two as proposed by Suykens et al. (1999). The comparison on computational speed of our method with the CG method proposed by Suykens et al. and the first order and second order SMO methods on several benchmark data sets shows a reduction of training time by up to 44%. (C) 2011 Elsevier B.V. All rights reserved.

An expression vector containing a rhamnose-inducible promoter provides tightly regulated gene expression in Burkholderia cenocepacia

Infection of the respiratory tract caused by Burkholderia cepacia complex poses a serious risk for cystic fibrosis (CF) patients due to the high morbidity and mortality associated with the chronic infection and the lack of efficacious antimicrobial treatments. A detailed understanding of the pathogenicity of B. cepacia complex infections is hampered in part by the limited availability of genetic tools and the inherent resistance of these isolates to the most common antibiotics used for genetic selection. In this study, we report the construction of an expression vector which uses the rhamnose-regulated P(rhaB) promoter of Escherichia coli. The functionality of the vector was assessed by expressing the enhanced green fluorescent protein (eGFP) gene (e-gfp) and determining the levels of fluorescence emission. These experiments demonstrated that P(rhaB) is responsive to low concentrations of rhamnose and it can be effectively repressed with 0.2% glucose. We also demonstrate that the tight regulation of gene expression by P(rhaB) promoter allows us to extend the capabilities of this vector to the identification of essential genes.

Genetic analysis of the O7-polysaccharide biosynthesis region from the Escherichia coli O7:K1 strain VW187

We recently cloned biosynthesis genes for the O7-lipopolysaccharide (O7-LPS) side chain from the Escherichia coli K-1 strain VW187 (M. A. Valvano, and J. H. Crosa, Infect. Immun. 57:937-943, 1989). To characterize the O7-LPS region, the recombinant cosmids pJHCV31 and pJHCV32 were mutagenized by transposon mutagenesis with Tn3HoHo1, which carries a promoterless lac operon and can therefore generate lacZ transcriptional fusions with target DNA sequences. Cells containing mutated plasmids were examined for their ability to react by coagglutination with O7 antiserum. The LPS pattern profiles of the insertion mutants were also investigated by electrophoresis of cell envelope fractions, followed by silver staining and immunoblotting analysis. These experiments identified three phenotypic classes of mutants and defined a region in the cloned DNA of about 14 kilobase pairs that is essential for O7-LPS expression. Analysis of beta-galactosidase production by cells carrying plasmids with transposon insertions indicated that transcription occurs in only one direction along the O7-LPS region. In vitro transcription-translation experiments revealed that the O7-LPS region encodes at least 16 polypeptides with molecular masses ranging from 20 to 48 kilodaltons. Also, the O7-LPS region in VW187 was mutagenized by homologous recombination with subsets of the cloned O7-LPS genes subcloned into a suicide plasmid vector. O7-LPS-deficient mutants of VW187 were complemented with pJHCV31 and pJHCV32, confirming that these cosmids contain genetic information that is essential for the expression of the O7 polysaccharide.

A Kernel Interleaved Scheduling Method for Streaming Applications on Soft-core Vector Processors

Massively parallel networks of highly efficient, high performance Single Instruction Multiple Data (SIMD) processors have been shown to enable FPGA-based implementation of real-time signal processing applications with performance and
cost comparable to dedicated hardware architectures. This is achieved by exploiting simple datapath units with deep processing pipelines. However, these architectures are highly susceptible to pipeline bubbles resulting from data and control hazards; the only way to mitigate against these is manual interleaving of
application tasks on each datapath, since no suitable automated interleaving approach exists. In this paper we describe a new automated integrated mapping/scheduling approach to map algorithm tasks to processors and a new low-complexity list scheduling technique to generate the interleaved schedules. When applied to a spatial Fixed-Complexity Sphere Decoding (FSD) detector
for next-generation Multiple-Input Multiple-Output (MIMO) systems, the resulting schedules achieve real-time performance for IEEE 802.11n systems on a network of 16-way SIMD processors on FPGA, enable better performance/complexity balance than current approaches and produce results comparable to handcrafted implementations.

A sequential algorithm for sparse support vector classifiers

Support vector machines (SVMs), though accurate, are not preferred in applications requiring high classification speed or when deployed in systems of limited computational resources, due to the large number of support vectors involved in the model. To overcome this problem we have devised a primal SVM method with the following properties: (1) it solves for the SVM representation without the need to invoke the representer theorem, (2) forward and backward selections are combined to approach the final globally optimal solution, and (3) a criterion is introduced for identification of support vectors leading to a much reduced support vector set. In addition to introducing this method the paper analyzes the complexity of the algorithm and presents test results on three public benchmark problems and a human activity recognition application. These applications demonstrate the effectiveness and efficiency of the proposed algorithm.


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BIT-LEVEL SYSTOLIC ARRAY CIRCUIT FOR MATRIX VECTOR MULTIPLICATION.

A bit-level systolic array for computing matrix x vector products is described. The operation is carried out on bit parallel input data words and the basic circuit takes the form of a 1-bit slice. Several bit-slice components must be connected together to form the final result, and authors outline two different ways in which this can be done. The basic array also has considerable potential as a stand-alone device, and its use in computing the Walsh-Hadamard transform and discrete Fourier transform operations is briefly discussed.

Reduced-memory multirate vector quantisation

A new method is proposed which reduces the size of the memory needed to implement multirate vector quantizers. Investigations have shown that the performance of the coders implemented using this approach is comparable to that obtained from standard systems. The proposed method can therefore be used to reduce the hardware required to implement real-time speech coders.

Systolic array system for vector quantization using transformed sub-band coding.

The use of bit-level systolic arrays in the design of a vector quantized transformed subband coding system for speech signals is described. It is shown how the major components of this system can be decomposed into a small number of highly regular building blocks that interface directly to one another. These include circuits for the computation of the discrete cosine transform, the inverse discrete cosine transform, and vector quantization codebook search.