A pipelined architecture is proposed for the normalized least mean square (NLMS) adaptive digital filter (ADF). Pipelined implementation of the NLMS has not yet been proposed. The proposed architecture is the first attempt to implement the NLMS ADF in the pipelined fashion. The architecture is based on an equivalent expression of the NLMS derived in this study. It is shown that the proposed architecture achieves a constant and a short critical path without producing output latency. In addition, it retains the advantage of the NLMS, i. e. , that the step size that assures the convergence is determined automatically. Computer simulation results that confirm that the proposed architecture achieves convergence characteristics identical to those of the NLMS.

In this letter, we propose a new error protection technique for JPEG2000-coded images and also present its evaluation over an OFDM channel. The method exploits the layer structure of the JPEG2000 codestream, a data embedding technique and a forward error correcting code. The main header and data in the top layer are duplicated and protected by the error correcting code. These data are then embedded into the bottom layer for error recovery purposes. Our method offers several features: preserves the same codestream structure as the one in the JPEG2000 part 1 standard, provides multilevel error protection, and can be combined with the existing error resilience technique. Hence, the method accommodates the new requirements for wireless JPEG2000 (JPWL/JPEG2000 part 11).

The main purpose of this paper is to give a new representation method of the convergence characteristics of the LMS algorithm using tap-input vectors. The described representation method is an extended version of the interpretation method based on the orthogonal projection. Using this new representation, we can express the convergence characteristics in terms of tap-input vectors instead of the eigenvalues of the input signal. From this representation, we consider a general method for improving the convergence speed.

A new gradient type adaptive algorithm is proposed in this paper. It is formulated based on the least squares criteria while the conventional gradient algorithms are based on the least mean square criteria. The proposed algorithm has two variable parameters and by changing them we can adjust the characteristic of the algorithm from the RLS to the LMS depending on the environment. This capability of adjustment achieves the possibility of providing better solutions. However, not only it provides better solutions than the conventional algorithms under some conditions but also it provides a very interesting theoretical view point. It provides a unified view point of the adaptive algorithms including the conventional ones, i.e., the LMS or the RLS, as limited cases and it enables us to analyze the bounds for those algorithms.

In this paper, we propose an extension to the image transport protocol (ITP). When images are transmitted through the Internet, TCP is generally used because it ensures the reliable transmission. However, interactivity will largely affected because of its acknowledgement scheme. This becomes remarkable in the network where packet-loss rate is relatively higher like wireless LANs. For more efficient image transmission, ITP was proposed. Like UDP, in ITP transmission, packets can be transmitted without acknowledgement of the reception. This contributes to improve the interactivity, on the other hand, some of packets may lost during transmission. ITP has a mechanism that the receiver-side can control the retransmission of the lost packets to maintain the quality of the received image. However, it is a hard task for the receiver to select which packets to be retransmitted. In this paper, we propose an extension to ITP by which the server can mark the importance of each packet. This helps the receivers to select important packets for requesting retransmission for server.

This paper propose a method for improving the image quality of motion estimation (ME) using low-bit images. By using edge-enhanced images for quantization, we can increase the accuracy of the ME and improve the image quality. It is known that using low-bit images for ME is effective for reducing power consumption but it slightly degrades image quality. The quality of the encoded image depends on the thresholds for data quantization, thus, algorithms for determining thresholds are studied. The proposed method uses linear quantization, which simply truncates the least significant bits. This method is simple without any complicated threshold calculations, and the resultant image quality is improved as much as the methods that use threshold calculations. To evaluate the effectiveness, we simulate results for image quality and estimate the power consumption using synthesis results from a VHDL model motion estimator.

In this paper we propose a new pipelined architecture for the LMS adaptive filter which can be implemented with less than half the amount of calculation needed for the conventional architectures. Even though the proposed architecture reduces the required calculation, it can simultaneously produce good convergence characteristics, a short latency and high throughput characteristics.

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.

We present a successful method for designing 2-D circularly symmetric R lowpass filters with constant group delay. The procedure is based on a transformation of a 1-D prototype R filter with constant group delay, whose magnitude response is the 2-D cross-sectional response. The 2-D filter transfer function has a separable denominator and a numerator which is obtained from the prototype numerator by means of a series of McClellan transformations whose free parameters can be optimized by successive procedure. The method is illustrated by an example.

JPEG2000 compression standard considers a block of wavelet coefficients, called codeblock, as the smallest coding unit that being independently entropy-coded. In this paper, we propose a codeblock-based concealment technique for JPEG2000 images to mitigate missing codeblock due to packet loss in network transmission. The proposed method creates a single JPEG2000 codestream from an image that composed of several subsampled versions of the original image and transmit the codestream over a single channel.The technique then substitutes the affected codeblock in a subsampled image with a copy of the corresponding codeblock obtained from other subsampled images. Thus, it does not require an iterative processing, which is time consuming, to construct an estimated version of the lost data. Moreover, it is applicable for a large codeblock size and can be implemented either in wavelet or codestream domain. Simulation results confirm the effectiveness of the proposed method.

A pipelined adaptive digital filter (ADF) architecture based on a two-dimensional least mean square algorithm is proposed. This architecture enables the ADF to be operated at a high clock rate and reduction of the required amount of hardware. To achieve this reduction we introduce a new building unit, called a block, and propose implementing the pipelined ADF using the block, Since the number of blocks in a cell is adjustable, we derive a condition for satisfying given specifications. We show the smallest number of blocks and the corresponding delay can be determined by using the proposed method.

In this paper, we propose a method which enables us to control the variance of the coefficients of the LMS-type adaptive filters. 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, at each time, we check if the updated value exists within the predefined range of distribution. The update of a coefficient will be canceled when its updated value exceeds the range. We propose an implementation method which has similar formula as the Gaussian mixture model (GMM) widely used in signal processing and machine learning. The effectiveness of the proposed method is evaluated by the computer simulations.

In this paper, we consider the selection of analysis filters used in the delayless subband adaptive digital filter (SBADF) and propose to use simple analysis filters to reduce the computational complexity. The coefficients of filters are determined using the components of the first order Hadamard matrix. Because coefficients of Hadamard matrix are either 1 or -1, we can analyze signals without multiplication. Moreover, the conditions for convergence of the proposed method is considered. It is shown by computer simulations that the proposed method can converge to the Wiener filter.

In this paper, we propose a novel QoS (Quality of Service) estimation scheme for JPEG 2000 coded image at RTP (realtime transfer protocol) layer without decoding the image. QoS of streaming video is estimated in view of several points, such as, transmission delay, or quality of received images. In this paper, we evaluate the QoS in terms of quality of received images. Generally, RTP is carried on top of UDP, and hence, quality of transmitted images could be degraded due to packet loss. To estimate the quality of received JPEG 2000 coded image without decoding, we use RTP header extension in order to send additional information to the receiver. The effectiveness of the proposed method is confirmed by the computer simulations.

In this paper, we propose two new pipelined adaptive digital filter architectures. The architectures are based on an equivalent expression of the least mean square (LMS) algorithm. It is shown that one of the proposed architectures achieves the minimum output latency, or zero without affecting the convergence characteristics. We also show that, by increasing the output latency be one, the other architecture can be obtained which has a shorter critical path.

In this paper, we propose the multirate repeating method for alias free subband adaptive filters (AFSAFs) and consider its convergence property. It is shown that we can adjust the convergence speed and the final error of the adaptive filters by varying its two parameters according to the requirements of the applications where the method is applied. The proposed method has two parameters, namely, the number of channel and the number of repetition. We show that by increasing the number of channels we can reduce the final error, and this property is preferred when the signal-to-noise ratio (SNR) is low. On the other hand, we show that the convergence speed of the AFSAF approaches to that of the affine projection algorithm (APA) by increasing the number of repetition. Through the computer simulations, we show the effect of the proposed method.

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 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., limitation on the filter type and on the filter bank structure. In this paper, development of this technique is presented. Consequently, any type of linear phase FIR filter and any structure of filter bank can be used.

A synthesis technique is presented for the multiple feedback (MF) active RC realization of transfer functions having complex frequency transmission zeros, and a biquadratic block in the MF structure is proposed, which is suitable for realizing the internal transfer function having complex zeros and poles.

Two design methods, namely method 1 and method 2, for class partial response FIR filters with equiripple stopband attenuation and low intersymbol interference (ISI) are investigated. For method 1, we design only a transmitter filter. For method 2, we design a transmitter and receiver filter pair having nearly the same amplitude response in the frequency domain. Both design methods have mainly three steps in common. First, a truncated sampled sequence of an ideal impulse response is used as an initial impulse response of the filter or filter pair in cascade. The optimum length of the sequence is examined. Second, z is transformed into such that the stopband section on the z-plane unit circle of the filter is mapped to be the entire unit circle in the -plane. Then a special all-zero function of is constructed having equiripple amplitude response along the unit circle. From this function, the filter transfer function of z with equiripple stopband attenuation is derived by inversely transforming into z. Finally, zero ISI approximation is performed with least-squares criterion, which drastically reduces ISI without significant change in the attenuation. Various characteristics of the filters designed by both methods are also illustrated.