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.

IMPROVED POSTFILTERING TECHNIQUE FOR BLOCK QUANTISATION OF SPEECH.

A modified comb filtering technique is proposed which can be used to reduce framing noise generated when speech signals are transform-coded or vector-quantized. Application of this filter to 9. 6 kbit/s speech in a vector transform coder has been found to improve the perceptual quality of the coded speech.

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.

Systolic building block for high performance recursive filtering

A novel bit level systolic array is presented that can be used as a building block in the construction of recursive digital filters. The circuit accepts bit-parallel input data, is pipelined at the bit level, and exhibits a very high throughput rate. The most important feature of the circuit is that it allows recursive operations to be implemented directly without incurring the large m cycle latency (where m is approximately the word length) normally associated with such systems. The use of this circuit in the construction of both first- and second-order IIR (infinite-impulse-response) filters is described.

Algorithms and architectures for high performance recursive filtering

Recently, a number of most significant digit (msd) first bit parallel multipliers for recursive filtering have been reported. However, the design approach which has been used has, in general, been heuristic and consequently, optimality has not always been assured. In this paper, msd first multiply accumulate algorithms are described and important relationships governing the dependencies between latency, number representations, etc are derived. A more systematic approach to designing recursive filters is illustrated by applying the algorithms and associated relationships to the design of cascadable modules for high sample rate IIR filtering and wave digital filtering.

VLSI architectures for vector quantization

The real time implementation of an efficient signal compression technique, Vector Quantization (VQ), is of great importance to many digital signal coding applications. In this paper, we describe a new family of bit level systolic VLSI architectures which offer an attractive solution to this problem. These architectures are based on a bit serial, word parallel approach and high performance and efficiency can be achieved for VQ applications of a wide range of bandwidths. Compared with their bit parallel counterparts, these bit serial circuits provide better alternatives for VQ implementations in terms of performance and cost. © 1995 Kluwer Academic Publishers.

High performance VLSI architecture for Wave Digital Filtering

The application of fine grain pipelining techniques in the design of high performance Wave Digital Filters (WDFs) is described. It is shown that significant increases in the sampling rate of bit parallel circuits can be achieved using most significant bit (msb) first arithmetic. A novel VLSI architecture for implementing two-port adaptor circuits is described which embodies these ideas. The circuit in question is highly regular, uses msb first arithmetic and is implemented using simple carry-save adders. © 1992 Kluwer Academic Publishers.

Bit-Level systolic architectures for high performance IIR filtering

Several novel systolic architectures for implementing densely pipelined bit parallel IIR filter sections are presented. The fundamental problem of latency in the feedback loop is overcome by employing redundant arithmetic in combination with bit-level feedback, allowing a basic first-order section to achieve a wordlength-independent latency of only two clock cycles. This is extended to produce a building block from which higher order sections can be constructed. The architecture is then refined by combining the use of both conventional and redundant arithmetic, resulting in two new structures offering substantial hardware savings over the original design. In contrast to alternative techniques, bit-level pipelinability is achieved with no net cost in hardware. © 1989 Kluwer Academic Publishers.

Pipelined two-port adaptor for wave digital filtering

The application of fine-grain pipelining techniques in the design of high-performance wave digital filters (WDFs) is described. The problems of latency in feedback loops can be significantly reduced if computations are organized most significant, as opposed to least significant, bit first and if the results are fed back as soon as they are formed. The result is that chips can be designed which offer significantly higher sampling rates than otherwise can be obtained using conventional methods. How these concepts can be extended to the more challenging problem of WDFs is discussed. It is shown that significant increases in the sampling rate of bit-parallel circuits can be achieved using most significant bit first arithmetic.

Bit-level systolic arrays for IIR filtering.

A novel bit-level systolic array architecture for implementing IIR (infinite-impulse response) filter sections is presented. A first-order section achieves a latency of only two clock cycles by using a radix-2 redundant number representation, performing the recursive computation most significant digit first, and feeding back each digit of the result as soon as it is available. The design is extended to produce a building block from which second- and higher-order sections can be connected.

Systolic VLSI compiler (SVC) for high performance vector quantisation chips

An overview is given of a systolic VLSI compiler (SVC) tool currently under development for the automated design of high performance digital signal processing (DSP) chips. Attention is focused on the design of systolic vector quantization chips for use in both speech and image coding systems. The software in question consists of a cell library, silicon assemblers, simulators, test pattern generators, and a specially designed graphics shell interface which makes it expandable and user friendly. It allows very high performance digital coding systems to be rapidly designed in VLSI.

Optimized bit level architectures for IIR filtering

Optimized circuits for implementing high-performance bit-parallel IIR filters are presented. Circuits constructed mainly from simple carry save adders and based on most-significant-bit (MSB) first arithmetic are described. Two methods resulting in systems which are 100% efficient in that they are capable of sampling data every cycle are presented. In the first approach the basic circuit is modified so that the level of pipelining used is compatible with the small, but fixed, latency associated with the computation in question. This is achieved through insertion of pipeline delays (half latches) on every second row of cells. This produces an area-efficient solution in which the throughput rate is determined by a critical path of 76 gate delays. A second approach combines the MSB first arithmetic methods with the scattered look-ahead methods. Important design issues are addressed, including wordlength truncation, overflow detection, and saturation.