42651
Analytical design of maximally flat FIR fractional Hilbert transformers
Recently, the classical Hilbert transformer is generalized into the fractional Hilbert transformer which could be implemented optically. This modification of the Hilbert transform adds an additional degree of freedom on the Hilbert transformer and improves the performance of the transform. In this paper, the design of FIR filters fractional Hilbert transformer is proposed. The FIR filters are designed in the maximally flat sense. The impulse responses of the filters are uniquely solved and expressed in simple analytic forms. The impulse responses can be exactly expressed as fixed point binary values. The resulting frequency responses approximate the ideal one very well in the middle-frequency band. Efficient hardware realization structures are obtained based on the symmetric properties of the impulse responses. Several design examples with various transform parameters and various filter orders are presented. Some examples of 1-D/2-D edge detection are given. The examples show that the proposed FIR filter can enhance the selected edges very efficiently.
41563247
Analytical design of digital nonrecursive maximally flat fractional Hilbert transformer
Recently, a generalization of the Hilbert transformer, the fractional Hilbert transformer, was defined and developed. In this paper, we propose a design of the FIR filter to realize the fractional Hilbert transformer based on the maximally flat approach. The impulse response is obtained explicitly. An efficient realization structure is constructed according to some properties of the impulse response.
17913196
Community Learning in Information Technology Fashion
In their striving to learn about information technology innovations, organizations draw on knowledge resources available in the diverse organizational communities that converge around those innovations. But even as such organizations learn about an innovation, so too does the larger community. Community learning takes place as its members reflect upon their learning and contribute their experiences, observations, and insights to the community’s on-going innovation discourse. Community learning and organizational learning thus build upon one another in a reciprocal process, or cycle, over time, as the stock of interpretations, adoption rationales, implementation strategies, and utilization patterns is expanded and refined. Relative to this overall cycle, we explore the neglected aspect that concerns how community learning draws on organizational learning. Analyzing the community discourse on enterprise resource planning (ERP) over the past 14 years, we found that different types of organizational actors played different roles, at different times, in contributing different types of knowledge to the discourse. Research analysts and technology vendors took leadership early on in articulating the know-what (conceptualization and interpretation) and know-why (justification) for ERP. Later on, adopters came to dominate the discourse through contributions of know-how (capacitation). We situate these observations in a larger model of the learning cycle, and outline a number of areas for future research on the crucial interactions between organizational and community learning in IT innovation.
31996759
Analysis and Design of Parallel Thinning Algorithms - A Generic Approach
In this paper, a generic approach for the analysis and design of parallel thinning algorithms is presented. The procedures for designing 4-subcycle/iteration, 2-subcycle/iteration, and 1-subcycle/iteration thinning algorithms are developed. The experimental results show that these thinning algorithms designed by proposed approach preserve image connectivity, produce thinner results, and obtain faster speed than many existing key thinning algorithms. As an example, a 1-subcycle/iteration algorithm and its experimental results were illustrated, which is in general about two times faster than others in the literature.
6086436
3D Line Image Analysis - A Heuristic Parallel Approach with Learning and Recognition
Abstract A heuristic parallel approach for (3d) line image analysis is introduced by using the concept of coordinated graph, layered graph representation, and parallel matching techniques and it significantly reduces the time required for dealing with three-dimensional line image analysis problems. Their fundamental properties and the concept of finite representations are investigated, and an interactive and iterative recognition algorithm with learning and recognition as a part of each other is presented. Several interested examples including curved and disconnected line images are illustrated. In addition to its importance in theoretical studies, this approach can also be applied to 3d object recognition, image processing, and computer vision in industrial, military, and medical fields.
22667475
High-performance IP routing table lookup
Nowadays, the commonly used table lookup scheme for IP routing is based on the so-called classless interdomain routing (CIDR). With CIDR, routers must find out the best matching prefix (BMP) for IP packets forwarding, which complicates the IP lookup. Currently, this process is mainly done in software and several schemes have been proposed for hardware implementation. Since the IP lookup performance is a major design issue for the new generation routers, in this article we propose a fast IP address lookup scheme, which significantly reduces the forwarding table to fit into SRAM with very low cost. It can also be implemented in hardware using the pipeline technique. By using our proposed method, the required memory space can be 90-170Kb less than the previous scheme and three memory accesses for a lookup in the worst case. When implemented in hardware pipeline architecture, our mechanism can achieve one routing lookup per memory access.
2857808
A knowledge-based segmentation algorithm for enhanced recognition of handwritten courtesy amounts
Abstract A knowledge-based segmentation algorithm to enhance recognition of courtesy amounts on bank checks is proposed in this paper. This algorithm uses multiple contextual cues to enhance segmentation and recognition. The system described extracts context from the handwritten numerals and uses a syntax parser based on a deterministic finite automaton to provide adequate feedback to enhance recognition. Further feedback is provided by a simple legal amount decoder that determines word count and recognizes several key words (e.g. thousand and hundred). This provides an additional semantic constraint on the dollar section. The segmentation analysis module presented is capable of handling a number of commonly used styles for courtesy amount representation. Both handwritten and machine written courtesy and legal amounts were utilized to test the efficacy of the preprocessor for the check recognition system described in this paper. The substitution error was reduced by 30–40% depending on the input check mix.