Adaptive Volterra filters (AVFs) are usually used to identify nonlinear systems, such as loudspeaker systems, and ordinary adaptive algorithms can be used to update the filter coefficients of AVFs. However, AVFs require huge computational complexity even if the order of the AVF is constrained to the second order. Improving calculation efficiency is therefore an important issue for the real-time implementation of AVFs. In this paper, we propose a novel sub-band AVF with high calculation efficiency for second-order AVFs. The proposed sub-band AVF consists of four parts: input signal transformation for a single sub-band AVF, tap length determination to improve calculation efficiency, switching the number of sub-bands while maintaining the estimation accuracy, and an automatic search for an appropriate number of sub-bands. The proposed sub-band AVF can improve calculation efficiency for which the dominant nonlinear components are concentrated in any frequency band, such as loudspeakers. A simulation result demonstrates that the proposed sub-band AVF can realize higher estimation accuracy than conventional efficient AVFs.

A novel scheduling method for asynchronous multirate/multi-task processing by programmable digital signal processors (DSPs) has been developed. This mixed scheduling method combines static and dynamic scheduling, and avoids runtime overheads due to interrupts in context switching to realizes asynchronous multirate systems. The processing delay introduced when using static scheduling with static buffering is avoided by introducing deadline scheduling in the static schedule design. In the developed software design system, a block-diagram description language is extended to describe asynchronous multi-task processing. The scheduling method enables asynchronous multirate processing, such as arbitrary-sampling-ratio rate conversion, asynchronous interface, and multimedia applications, to be efficiently realized by programmable DSPs.

Several subband array methods have been proposed as useful means to perform joint spatio-temporal equalization in digital mobile communications. These methods can be applied to mitigate problems caused by the inter-symbol interference (ISI) and co-channel interference (CCI). The subband array methods proposed so far can be classified into two major schemes: (1) a centralized feedback scheme and (2) a localized feedback scheme. In this paper, we propose subband arrays with partial feedback scheme, which generalize the above two feedback schemes. The main contribution of this paper is to derive the steady-state mean square error (MSE) performance of subband arrays implementing these three different feedback schemes. Unlike the centralized feedback scheme which can be designed to provide the optimum equalization performance, the subband arrays with localized and partial feedback schemes are in general suboptimal. The performance of these two suboptimal feedback schemes depends on the channel characteristics, the filter banks employed, and the number of subbands.

Block delay caused by using fast Fourier transform (FFT), and computational complexity in sampling rate conversion system are considered in this paper. The relationship between the number of block delays and the computational complexity is investigated. The proposed method can avoid the redundant operations of sampling rate conversion completely and moreover provide a good trade-off between the number of block delays and the computational complexity. As a result, ti is shown that with the proposed method, the sampling rate conversion can be realized more efficiently under a small number of block delays.

Conventional subband ADF's (adaptive digital filters) using filter banks have shown a degradation in performance because of the non-ideal nature of filters. To solve this problem, we propose a new type of subband ADF incorporating two types of analysis filter bank. In this paper, we show that we can design the optimum filter bank which minimizes the LMSE (least mean squared error). In other words, we can design a subband ADF with less MSE than that of conventional subband ADF's.

This paper describes a system that can enchance the speech quality degradation due to severe band limitation during speech transmission. We have already proposed a spectrum widening method that utilizes aliasing in sampling rate conversion and digital filtering for spectrum shaping. This paper proposes a new method that offers improved performance in terms of the spectrum distortion characteristics. Implementation procedures are clarified, and its performance is discussed. The proposed method can effectively enhance speech quality.

In this paper, we propose two parallel processing methods for multidimensional (MD) sampling lattice alteration. The use of our proposed methods enables us to alter the sampling lattice of a given MD signal sequence in parallel without any redundancy caused by up- and down-sampling, even if the alteration is rational and non-separable. Our proposed methods are provided by extending two conventional block processing techniques for FIR filtering: the overlap-add method and the overlap-save method. In these proposed methods, firstly a given signal sequence is segmented into some blocks, secondly sampling lattice alteration is implemented for each block data individually, and finally the results are fitted together to obtain the output sequence which is identical to the sequence obtained from the direct sampling lattice alteration. Besides, we provide their efficient implementation: the DFT-domain approach, and give some comments on the computational complexity in order to show the effectiveness of our proposed methods.