Wavelet Transform for Forward and Inverse

In this research, an architecture that performs both forward and inverse lifting-based discrete wavelet transform is proposed. The proposed architecture reduces the hardware requirement by exploiting the redundancy in the arithmetic operation involved in DWT computation. The proposed architecture does not require any extra memory to store intermediate results. The proposed architecture consists of predict module, update module, address generation module, control unit and a set of registers to establish data communication between predict and update modules. The symmetrical extension of images at the boundary to reduce distorted images has been incorporated in our proposed architecture as mentioned in JPEG2000. This architecture has been described in VHDL at the RTL level and simulated successfully using Model Sim simulation environment

Data Mining Tools and Techniques: a review

Data mining automates the detection of relevant patterns in a database, using defined approaches andalgorithms to look into current and historical data that can then be analyzed to predict future trends.Because data mining tools predict future trends and behaviors by reading through databases for hiddenpatterns, they allow organizations to make proactive, knowledge-driven decisions and answer questions thatwere previously too time-consuming to resolve. The data mining methods such as clustering, associationrules, sequential pattern, statistics analysis, characteristics rules and so on can be used to find out the usefulknowledge, enabling such data to become the real fortune of logistics companies and support theirdecisions and development. This paper introduces the significance use of data mining tools and techniquesin logistics management system, and its implications. Finally, it is pointed out that the data miningtechnology is becoming more and more powerful in logistics management.Keywords: Logistics management, Data Mining concepts, application areas, Tools and Technique