1283699
ConvexSmooth: a simultaneous convex fitting and smoothing algorithm for convex optimization problems
Convex optimization problems are very popular in the VLSI design society due to their guaranteed convergence to a global optimal point. Table data is often fitted into analytical forms like posynomials to make them convex. However, fitting the look-up tables into posynomial forms with minimum error itself may not be a convex optimization problem and hence excessive fitting errors may be introduced. In recent literature numerically convex tables have been proposed. These tables are created optimally by minimizing the perturbation of data to make them numerically convex. But since these tables are numerical, it is extremely important to make the table data smooth, and yet preserve its convexity. Smoothness will ensure that the convex optimizer behaves in a predictable way and converges quickly to the global optimal point. In this paper, we propose to simultaneously create optimal numerically convex look-up tables and guarantee smoothness in the data. We show that numerically "convexifying" and "smoothing" the table data with minimum perturbation can be formulated as a convex semidefinite optimization problem and hence optimality can be reached in polynomial time. We present our convexifying and smoothing results on industrial cell libraries. ConvexSmooth shows 14times reduction in fitting error over a well-developed posynomial fitting algorithm
35912465
An Algorithm for Trading Off Quantization Error with Hardware Resources for MATLAB-Based FPGA Design
Most practical FPGA designs of digital signal processing (DSP) applications are limited to fixed-point arithmetic owing to the cost and complexity of floating-point hardware. While mapping DSP applications onto FPGAs, a DSP algorithm designer must determine the dynamic range and desired precision of input, intermediate, and output signals in a design implementation. The first step in a MATLAB-based hardware design flow is the conversion of the floating-point MATLAB code into a fixed-point version using "quantizers" from the filter design and analysis (FDA) toolbox for MATLAB. This paper describes an approach to automate the conversion of floating-point MATLAB programs into fixed-point MATLAB programs, for mapping to FPGAs by profiling the expected inputs to estimate errors. Our algorithm attempts to minimize the hardware resources while constraining the quantization error within a specified limit. Experimental results on five MATLAB benchmarks are reported for Xilinx Virtex II FPGAs.
6457662
ConvexFit: an optimal minimum-error convex fitting and smoothing algorithm with application to gate-sizing
Convex optimization has gained popularity due to its capability to reach global optimum in a reasonable amount of time. Convexity is often ensured by fitting the table data into analytically convex forms such as posynomials. However, fitting the look-up tables into the posynomial forms with minimum error itself may not be a convex optimization problem and hence excessive fitting errors may be introduced. In this paper, we propose to directly adjust the look-up table values into a numerically convex look-up table without explicit analytical form. We show that numerically "convexifying" the table data with minimum perturbation can be formulated as a convex semidefinite optimization problem and hence optimality can be reached in polynomial time. Without an explicit form limitation, we find that the fitting error is significantly reduced while the convexity is still ensured. As a result, convex optimization algorithms can still be applied. Furthermore, we also develop a "smoothing" algorithm to make the table data smooth and convex to facilitate the optimization process. Results from extensive experiments on industrial cell libraries demonstrate that our method reduces 30/spl times/ fitting error over a well-developed posynomial fitting algorithm. Its application to circuit tuning is also presented.
26846276
Hierarchical representation of digitized curves through dominant point detection
Hierarchical data structures play a key role in representation of spatial data. This paper proposes an algorithm for constructing hierarchical representations of digitized curves based on the dominant points of the curve. The comparison of the proposed scheme with the other hierarchical representation schemes viz. Arc Tree and Strip Tree reveals that the proposed algorithm is generally better than the Arc Tree and compares well with the Strip Tree scheme.
9930427
An algorithm for converting floating-point computations to fixed-point in MATLAB based FPGA design
Most practical FPGA designs of digital signal processing applications are limited to fixed-point arithmetic owing to the cost and complexiry of floating-point hardware. While mapping DSP applications onto FPGAs, a DSP algorithm designer, who often develops his applications in MATLAB, must determine the dynamic range and desired precision of input, intermediate and output signals in a design implementation to ensure that the algorithm fidelity criteria are met. The first step in a flow to map MATLAB applications into hardware is the conversion of the floating-point MATLAB algorithm into a fixed-point version. This paper describes an approach to automate this conversion, for mapping to FPGAs by profiling the expected inputs to estimate errors. Our algorithm attempts to minimize the hardware resources while constraining the quantization error within a specified limit
3191837
Active 3-D Object Recognition Using Appearance-Based Aspect Graphs
We present a new active active recognition scheme (using an uncalibrated camera) based on a new idea, appearancebased aspect graphs. The scheme is robust to background clutter, and affine transformations of the object. We use a probabilistic reasoning framework which helps in probability calculations and planning the next view (when a view of the object does not contain sufficient features to recognise it unambiguously), in conjunction with a new hierarchical knowledge representation scheme. Preliminary experiments with the system show encouraging results.
27759262
Automatic categorization of web sites based on source types
An important issue with the Web is verification of the accuracy, currency and authenticity of the information associated with Web sites. One way to address this problem is to identify the "source" or "sponsor" of the Web site. However, source identification is non-trivial because the source of a Web site cannot always be determined by the URL or content of the site. In this paper, we propose a method for source identification that uses various types of inbound, outbound and internal interactions that arise due to hyperlinks between and within Web sites.
11274155
Minimum-Energy Broadcast Using Practical Directional Antennas in All-Wireless Networks
Energy-efficient broadcast communication is an important problem in wireless ad hoc networks. Previously, minimum-energy broadcast that exploits the broadcast nature of radio transmission has been studied and shown to be NP-complete for omnidirectional antennas. In this paper, we investigate the minimum-energy broadcast problem under a wide spectrum of directional antenna models, including sectored antennas with fixed sectors and beamwidth and antenna array-based smart antennas with varying degrees of beam orientation and beamwidth. We first propose the RF design and implementation of each model, which suggests the practical parameters of antennas under that model. We then show that the minimum-energy broadcast problem under each of the antenna models is NP-complete. Lastly, we present a heuristic algorithm based on BIP for the above problem under each directional antenna model and experimentally compare the energy efficiency of using different directional antennas using these heuristics. Our results show that using antennas with adjustable orientation and variable beamwidth gives the best results. For such antennas, the scanning angle is the dominant factor in improving the quality of the broadcast trees. The number of antennas per node is not that critical to obtaining a better broadcast tree as long as it is large enough to cover the entire 360◦ around a node so as to prevent network partitioning.
12929901
Completeness of Neighbourhood Logic
This paper presents a completeness result for a first-order interval temporal logic, called Neighbourhood Logic (NL) which has two neighbourhood modalities. NL can support the specification of liveness and fairness properties of computing systems as well as formalisation of many concepts of real analysis. These two modalities are also adequate in the sense that they can derive other important unary and binary modalities of interval temporal logic. We prove the completeness result for NL by giving a Kripke model semantics and then mapping the Kripke models to the interval models for NL.
13205673
Automatic Generation of Domain Models for Call-Centers from Noisy Transcriptions
Call centers handle customer queries from various domains such as computer sales and support, mobile phones, car rental, etc. Each such domain generally has a domain model which is essential to handle customer complaints. These models contain common problem categories, typical customer issues and their solutions, greeting styles. Currently these models are manually created over time. Towards this, we propose an unsupervised technique to generate domain models automatically from call transcriptions. We use a state of the art Automatic Speech Recognition system to transcribe the calls between agents and customers, which still results in high word error rates (40%) and show that even from these noisy transcriptions of calls we can automatically build a domain model. The domain model is comprised of primarily a topic taxonomy where every node is characterized by topic(s), typical Questions-Answers (Q&As), typical actions and call statistics. We show how such a domain model can be used for topic identification of unseen calls. We also propose applications for aiding agents while handling calls and for agent monitoring based on the domain model.