In this paper, we propose a method to lower the variance of the coefficients of the LMS-type adaptive filters in the noisy environments. In the method, each coefficient of the adaptive filter is modeled as an random variable with a Gaussian distribution, and its value is estimated as the mean value of the distribution. Besides, when updating each coefficient, we check if the updated value exists within the distribution. We do not update the coefficient value if it exceeds the range of the Gaussian distribution. We describe the theoretical basis of the method, and propose an implementation method which has similar formula as the Gaussian mixture model (GMM) widely used in video, or speech processing. The effectiveness of the proposed method is evaluated by the computer simulations.

Along with the rapid evolution of cloud computing, outsourcing service has also changed significantly. One of the main concerns for cloud computing is security. In particular, it becomes more important to handle client data securely in such a consulting service. In this paper, we present the design and implementation of Software as a Service (SaaS) application framework using Information Gateway that enables cloud service while maintaining data confidentiality. By setting up Information Gateway in the client environment, the executing location is dynamically controlled according to whether the data contains confidential information or not, and only secured data is routed to the SaaS application in the cloud. Therefore, if the data policy is registered by the client administrator beforehand, the user is able to use the cloud service appropriately without being aware of it. Moreover, we also describe that existing applications can be easily ported into the SaaS application because our framework allows application developers to define complicated routing logic briefly.

In this paper, we propose a no-reference (NR) method for estimating the degradation of Motion JPEG2000 (MJP2) video due to packet loss. The proposed method estimates the peak signal-to-noise ratio (PSNR) between received MJP2 frames affected by packet loss and the originally encoded frames without having information about the latter. The PSNR of a frame could be estimated in the wavelet domain, namely before the JPEG2000 decoding process, by utilizing adjacent frames that possess similar amounts of wavelet energy. Simulation results showed that the estimated PSNR is very close to the true value obtained by the full-reference calculation. Our method can be used to monitor the video quality in an IP-based transmission of MJP2, as well as for automatic judgment of error control in streaming applications, or in video broadcasting. For example, if the PSNR of a frame does not reach a predefined level, the frame will be rejected before the decoding process or it will be processed by a concealment techniques before being displayed.

This paper proposes an efficient packet loss protection strategy for transmission of JPEG2000 coded images over a packet erasure channel that backwardly compatible with the JPEG2000 part-1 decoder. The proposed scheme utilizes FEC at packet-level, the JPEG2000 layered structure and its error resilient functionalities. Prior to transmission, packets containing initial layers of the code-stream, which is associated lo a minimum acceptable image quality, are protected using a packet-level FEC. With a slight modification in the SOT marker segment and careful placement of the redundant packets, the generated codestream that carried redundant data is compliant with a standard decoder.

This paper proposes a fast implementation technique for RLS adaptive filters. The technique has an adjustable parameter to trade the throughput and the rate of convergence of the filter according to the applications. The conventional methods for improving the throughput do not have this kind of adjustability so that the proposed technique will expand the area of applications for the RLS algorithm. We show that the improvement of the throughput can be easily achieved by rearranging the formula of the RLS algorithm and that there are no need for faster PEs for the improvement.

This paper proposes an adaptive algorithm, which can be pipelined, as an extension of the delayed least mean square (DLMS) adaptive algorithm. The proposed algorithm provides a capability to achieve high throughput with less degradation of the convergence characteristic than the DLMS algorithm. An architecture for pipelined implementation of the proposed algorithm is considered, and based on this, the conditions for the implementation are derived. An efficient implementation of the architecture with less hardware is also considered.

We propose a method for achieving both a fast convergence speed and the low orders of adaptive digital filters (ADFs) for subband ADFs. The proposed method is based on the multirate repeating method which uses wasted signals by downsampling. First we show how to apply the multirate repeating method to the standard structure of subband ADFs. Next we consider a new structure of subband ADFs for extending the multirate repeating method. Finally, we show the validity of the proposed method by computer simulations.

The proposed algorithm updates filter coefficients using the time averaged gradient vectors and it ensures the good performance under noisy conditions and under finite precision implementation. It is shown that we can update the filter coefficients as many as the algorithm requires to converge even if only short data are available so that the proposed algorithm can converge faster than other gradient type algorithms, i.e. the LMS algorithm. Moreover, LMS algorithm can be regarded as a special case of the proposed algorithm and the tracking ability of the algorithm is shown.>

This paper describes a technique for improving the convergence speed of the LMS algorithm. The main idea of the technique is to increase the number of updatings of the filter weights per unit time so that the convergence speed is accelerated according to the number of updatings. The validity of the technique is shown by considering the deriving process of the LMS algorithm from the steepest descent algorithm. We present the two example structures for implementing the technique in actual applications. Finally we show the results of computer simulations.>

Describes the development of a technique for subband image coding called the symmetric extension method which utilizes the nature of a symmetrically extended image to achieve high quality coding. There are, however, some restrictions on the usable subband coding system. The development is done based on the property of a symmetrically extended signal in the analysis process to remove the restriction. The behavior of the sequence after two processes, filtering and decimation, is examined and formulated. The development extends the application area of the technique.

One of the problems with subband image coding is the increase in image sizes caused by filtering. To solve this, it has been proposed to process the filtering by transforming an input sequence into a periodic one. Then, filtering is implemented by circular convolution. Although this technique solves the problem, there are very strong restrictions, i.e. limitations on the filter type and on the filter bank structure. The development of this technique is presented. Consequently, any type of linear-phase finite impulse response (FIR) filter and any structure of filter bank can be used.>