We present a new family of algorithms that solve the bias problem in the equation-error based adaptive infinite impulse response (IIR) filtering. A novel constraint, called the constant-norm constraint, unifies the quadratic constraint and the monic one. By imposing the monic constraint on the mean square error (MSE) optimization, the merits of both constraints are inherited and the shortcomings are overcome. A new cost function based on the constant-norm constraint and Lagrange multiplier is defined. Minimizing the cost function gives birth to a new family of bias-free adaptive IIR filtering algorithms. For example, two efficient algorithms belonging to the family are proposed. The analysis of the stationary points is presented to show that the proposed methods can indeed produce bias-free parameter estimates in the presence of white noise. The simulation results demonstrate that the proposed methods indeed produce unbiased parameter estimation, while being simple both in computation and implementation.

We have proposed and implemented a spread spectrum (SS) wireless switch using 2.4 GHz front-end AlN/Al2O3 surface acoustic wave (SAW) matched filter (MF). Since the SAW MF has radio frequency (RF) front-end operation, RF components are not needed in the received circuit. High impedance in the peripheral circuit using passive devices has been employed for low current consumption. The SS wireless switches have been designed with the power consumption of less than 100 µW by using the SAW MF. It is confirmed that implemented SS wireless switch has a long battery life of 10 years and communication range of 30 m.

In this paper, a Wiener filtering method in wavelet domain is proposed for restoring an image corrupted by additive white noise. The proposed method utilizes the multiscale characteristics of wavelet transform and the local statistics of each subband. The size of a filter window for estimating the local statistics in each subband varies with each scale. The local statistics for every pixel in each wavelet subband are estimated by using only the pixels which have a similar statistical property. Experimental results show that the proposed method has better performance over the Lee filter with a window of fixed size.

We have proposed the packet SS-CDMA scheme for downlink of SS-CDMA flexible wireless cellular network. Transmission packet is framed with synchronization block with 11 chip Barker code and information block with orthogonal spreading code. The chip synchronization is carried out using short code surface acoustic wave (SAW) matched filter. The code de-spreading is carried out using in-line de-spreader. Multi-channel downlink of 63 channels can be designed using orthogonal m-sequence. Simulation results show more than 15 channels without degradation from theoretical value can be used under multi-path environment. The packet SS-CDMA modem has been implemented using a 2.4 GHz front-end SAW matched filter. Degradation of Eb/N0 of less than 0.5 dB is experimentally achieved with four-channel multiplex.

To achieve a sound field reproduction system, it is important to design multichannel inverse filters which cancel the effects of room transfer functions. The design method in the frequency domain based on the least-norm solution (LNS) requires less memory and less calculation than the design method in the time domain. However, the LNS method cannot guarantee the causality or stability of the filters. In this paper, a design method of a time-domain inverse filter using iterative processing in the frequency domain for multichannel sound field reproduction is proposed, and the result of numerical analysis is described. The proposed method can decrease the squared error of every control point by 3-12 dB. Furthermore, the sound reproduced by this method attains over 13 dB improvement in the segmental signal-noise ratio (SNR) compared with that designed by the LNS method for real environment impulse responses.

A new speech enhancement technique is proposed assuming that a speech signal is represented in terms of a linear probabilistic process and that a noise signal is represented in terms of a stationary random process. Since the target signal, i.e., speech, cannot be represented by a stationary random process, a Wiener filter does not yield an optimum solution to this problem regarding the minimum mean variance. Instead, a Kalman filter may provide a suitable solution in this case. In the Kalman filter, a signal is represented as a sequence of varying state vectors, and the transition is dominated by transition matrices. Our proposal is to construct the state vectors as well as the transition matrices based on time-frequency pattern of signals calculated by a wavelet transformation (WT). Computer simulations verify that the proposed technique has a high potential to suppress noise signals.

Most natural images are well modeled as smoothed areas segmented by edges. The smooth areas can be well represented by a wavelet transform with high regularity and with fewer coefficients which requires highpass filters with some vanishing moments. However for the regions around edges, short highpass filters are preferable. In one recently proposed approach, this problem was solved by switching filter banks using longer filters for smoothed areas of the images and shorter filters for areas with edges. This approach was applied to lossy image coding resulting in a reduction of ringing artifacts. As edges were predicted using neighboring pixels, the nonlinear transforms made the decorrelation more flexible. In this paper we propose a time-varying filterbank and apply it to lossless image coding. In this scheme, we estimate the standard deviation of the neighboring pixels of the current pixel by solving the maximum likelihood problem. The filterbank is switched between three filter banks, depending on the estimated standard deviation.

A simplified analysis is presented for the reverse link maximum capacity trade-offs between each layer, spectrum efficiency and its multi-rate features of TDMA/W-CDMA and N-CDMA/W-CDMA overlaid systems with the perfect power control based on the measurement of signal-to-interference ratio (CIR). In order to suppress the multi-cross interference, the other important techniques used in the analysis are the ideal notch filtering and the signal level clipper for W-CDMA system transmitters and receivers. We firstly propose the concepts of the notch filtering depth and signal level clipping depth in the paper. The numerical results can be adopted as a guideline in designing the overlaid systems in the various cases as well as a means to investigate the flexibility of sharing of the spread spectrum and their feasibility in the future mobile communication system.

In this paper, a novel cumulant-based adaptive notch filtering technique for the enhancement and tracking of a single sinusoid in additive noise is presented. In this technique, the enhanced signal is obtained as the output of a narrow bandpass filter implemented using a second-order pole-zero constraint IIR adaptive notch filter, which needs only one coefficient to be updated. The filter coefficient, which leads to identifying and tracking the sinusoidal frequency, is updated using a suggested adaptive algorithm employing a recursive estimate of the kurtosis and only one-sample-lag point of a selected one-dimensional fourth-order cumulant slice of the input signal. Therefore, the proposed technique provides automatically resistance to additive Gaussian noise. It is also shown that the presented technique outperforms the correlation-based counterpart in handling additive non-Gaussian noise. Simulation results are provided to show the effectiveness of the proposed algorithm in comparison with the correlation-based lattice algorithm.

Recently, in the modem, the spread spectrum communication system and the software radio, Digital Signal Processor type Squaring Loop (DSP-squaring-loop) is employed in the demodulation of Binary Phase Shift Keying (BPSK) signal. The DSP-squaring-loop extracts the carrier signal that is used for the coherent detection. However, in case the Signal to Noise Ratio (SNR) is low, the DSP-Phase Locked Loop (DSP-PLL) can not pull in the frequency offset and the phase offset. In this paper, we propose a DSP-squaring-loop that is robust against noise and which uses the adaptive notch filter type frequency estimator and the adaptive Band Pass Filter (BPF). The proposed method can extract the carrier signal in the low SNR environment. The effectiveness of the proposed method is confirmed by the computer simulation results.

We have proposed a current-cut switched-current matched filter (CC-SIMF) for direct-sequence code-division multiple-access (DS-CDMA). The 256-chip CC-SIMF can achieve low power consumption of less than 10 mW under high-speed operation of more than 16 Mcps. To reduce the current transfer error accumulation, we propose a parallel SIMF configuration. A 128-chip SIMF using 0.8-µm Complementally Metal Oxide Semiconductor (CMOS) process has been designed and fabricated. Optimization of the current memory cell structure has been described. The correlation operation at 16 Mcps has been obtained using a 128-chip orthogonal m-sequence. The code phase separation performance for path diversity has been clearly observed. The power consumption has been significantly reduced using the current-cut method.

In this study, we consider a filtering method for image sequence degraded by additive Gaussian noise and/or impulse noise (i.e., mixed noise). For removing the mixed noise from the 1D/2D signal, weighted median filters are well known as a proper choice. We have also proposed a filtering tool based on the weighted median filter with a data-dependent method. We call this data-dependent weighted median (DDWM) filters. Nevertheless, the DDWM filter, its weights are controlled by some local information, is not enough performance to restore the image sequence degraded by the noise. The reason is that the DDWM filter is not able to obtain good filtering performance both in the still and moving regions of an image sequence. To overcome above drawback, we add motion information as a motion detector to the local information that controls the weights of the filters. This new filter is proposed as a Video-Data Dependent Weighted Median (Video-DDWM) filter. Through some simulations, the Video-DDWM filter is shown to give effective restoration results than that given by the DDWM filtering and the conventional filtering method with a motion-conpensation (MC).

In this paper we propose a new simplified algorithm for cascaded second order adaptive notch filters implemented using an allpass filter, for elimination of multiple sinusoids. Each of the stages of the notch filter is implemented using direct form second order allpass filter. We also present an analysis which compares the proposed algorithm with the conventional simplified algorithm, and which indicates that the proposed algorithm has a reduced bias in the estimation of the multiple input sinusoids. Simulation results that have been provided confirm this analysis.

It is well known that based on the structure of a transversal filter, the RLS equaliser provides the fastest convergence in stationary environments. This paper addresses an adaptive transversal equaliser which has the potential to provide more faster convergence than the RLS equaliser. A comparison is made with respect to computational complexity required for each update of equaliser coefficients, and computer simulations are demonstrated to show the superiority of the proposed equaliser.

The paper proposes a transmitter diversity scheme with a desired signal selection for the mobile communication systems in which the severe cochannel interference (CCI) is assumed to occur at the base station. The feature of the proposed scheme is that the criterion of the downlink branch selection is based on the desired signal power estimated by the correlation between the received signal and the unique word at the matched filter. Moreover, the unique word length control method according to the instantaneous SIR is applied to the proposed scheme, taking account of the uplink transmission efficiency. Computer simulation results show that the proposed scheme provides the better performance than the conventional transmitter diversity in the severe CCI environments, and that the unique word length control method applied to the proposed scheme decreases the unique word length without the degradation of the transmission quality, comparing with the fixed unique word length method.

This paper presents adaptive image enhancement algorithms which enhance hidden signals in the pictures and describes their implementation for real-time video signals. An image enhancement algorithm proposed by T. Peli and J. S. Lim is extended for application to video signals. A fast implementation algorithm is provided with parallel implementation. The proposed algorithms are shown to be realized in real-time on 200 MHz microprocessors with multimedia extensions for 720 480 (pixels) 30 frames/sec video signals.

Improvement of direct sequence spread spectrum (DSSS) communication systems' performance using a lattice based adaptive infinite impulse response (IIR) notch filter with a simplified adaptation algorithm is presented. The improvement is shown to be achieved by rejection of a narrowband interference in a received DSSS binary phase shift keying (BPSK) signal. Sources of noise generated by an adaptive IIR notch filter are also studied. Apart from noise associated with input additive white gaussian noise, noise attributed to leakage sinusoids due to fluctuation of steady-state variable coefficient is also analysed. Using statistical properties of notch filter and pseudonoise (PN) correlator outputs, improvement of the performance of a DSSS system gained by the use of interference rejection filter is shown. Computer simulation results are used to confirm analytically derived expressions.

This paper presents a new data hiding scheme under fractal image generation via Fourier filtering method for Computer Graphics (CG) applications. The data hiding operations are achieved in the frequency domain and a method similar to QAM used in digital communication is introduced for efficient embedding in order to explore both phase and amplitude components simultaneously. Consequently, this scheme enables us not only to generate a natural terrain surface without loss of fractalness analogous to the conventional scheme, but also to embed larger amounts of data into an image depending on the fractal dimension. This scheme ensures the correct decoding of the embedded data under lossy data compression such as JPEG by controlling the quantization exponent used in the embedding process.

This paper proposes an algorithm that adaptively estimates time-varying noise variance used in Kalman filtering for real-time speech signal enhancement. In the speech signal contaminated by white noise, the spectral components except dominant ones in high frequency band are expected to reflect the noise energy. Our approach is first to find the dominant energy bands over speech spectrum using LPC. We then calculate the average value of the actual spectral components over the high frequency region excluding the dominant energy bands and use it as the noise variance. The resulting noise variance estimate is then applied to Kalman filtering to suppress the background noise. Experimental results indicate that the proposed approach achieves a significant improvement in terms of speech enhancement over those of the conventional Kalman filtering that uses the average noise power over silence interval only. As a refinement of our results, we employ multiple-Kalman filtering with multiple noise models and improve the intelligibility.

In this letter, we propose a robust adaptive filter with a Variable Forgetting Factor (VFF) for impulsive noise suppression. The proposed method can restrict the perturbation of the parameters using M-estimator and adaptively reduce the error propagation caused by the impulsive noise using VFF. Simulations show that the performance of the proposed algorithm is less vulnerable to the impulsive noise than those of the conventional Kalman filter based algorithms.