Anaesthesia is a medical act which eliminates the feeling of pain as well as the motor reactions of a person, before performing a surgical operation. Loco-Regional Anaesthesia (LRA) concerns only a part of the body such as the front arm or leg. This practice is increasingly used today notably because the patient can remain conscious and can recover more rapidly. However, LRA still remains a risky procedure. In this paper, we introduce a novel medical simulator called SAILOR for the training for LRA with neurostimulation. SAILOR is based on desktop virtual reality, realistic 3-D rendering and interactive techniques with a classical mouse and keyboard. It simulates the various biological phenomena which can occur during an anaesthesia procedure. We also introduce a novel pseudo-haptic effect to enhance the palpation of the virtual patient's body and feel the inner organs. The first feedback from users of the commercialized DVD version of SAILOR as well as the results of pilot tests suggest that this simulator is a very promising tool for education and training for LRA.

This paper describes a full-rate (FR) candidate speech codec for a new Adaptive Multi-Rate (AMR) codec standard. The proposed codec is a multi-rate codec, operating in various modes that have different bit-rate partitionings between source and channel coding. The source coding is based on Algebraic Code Excited Linear Predictive Coding (ACELP). Convolutional coding is used for the channel coding. Subjective tests show that at poor channel error conditions with low C/I-ratios of 7 dB, the lowest mode of the proposed codec produces speech quality comparable to G.728 in clean channel condition. The codec also provides substantial improvement on error robustness over the Enhanced Full Rate (EFR) GSM codec, by selecting an optimal coding rate to suit the channel condition. The codec performance passes twenty-six out of the twenty-nine test conditions, conducted according to [2]. Therefore, the proposed codec has passed the ETSI qualification test.

In this paper we present a new robust adaptive algorithm. It is derived from the standard QR decomposition based RLS (QRD-RLS) algorithm by introducing a non-orthogonal transform into the update recursion. Instead of updating an upper triangular matrix, as it is the case for the QRD-RLS, we adapt an upper triangular block diagonal matrix. The complexity of the algorithm, thus obtained, varies from O(N/sup 2/) to O(N) when the size of the diagonal blocks decreases. Simulations of the new algorithm have shown a better robustness than the standard QRD-based algorithm in the context of multichannel adaptive filtering with highly inter-correlated channels.

A significant drawback of the least mean square (LMS) algorithm is slow convergence speed when the input covariance matrix is ill-conditioned. Two structures are presented and studied for increasing the convergence speed for this case. The structures incorporate a prewhitening filter prior to the usual LMS adaptation. When the prewhitening filter is also adaptive the input to the LMS algorithm is nonstationary. An analysis of the coupling effect between the two adaptive algorithms show that the adaptive prewhitener has the capability of significantly speeding up to LMS adaptation as compared to a system without prewhitening. When the prewhitening filter is fixed (nonadaptive), the structure is shown to be equivalent to the filtered-X LMS algorithm. Stability conditions and transient means behavior are given in the time domain, in terms of the parameters of the pre-whitening filter.>

In order to avoid the coding noise accumulation in successive transcoders, a new fully digital structure is used where all the filters have quantized inputs. Whereas the coding noise spectrum is flat with the CCITT algorithm, with this new structure it presents a spectral shaping which can be further improved in high-frequency region, by filtering the quantizing noise.>

The unfavorable effects of narrowband inputs on the decoder adjustment when the LMS algorithm is used are analyzed. An explanation is given for the behavior of the CCITT algorithm. Suboptimality of prediction is granted to achieve adjustment, resulting in a satisfactory tradeoff between reduction rate and adjustment. The link between adjustment and uniform stability is enhanced.>

An analysis is presented of the causes of the accumulation of quantizing noise found in the transient state for successive CCITT adaptive differential pulse-code-modulation (ADPCM) transcoders connected synchronously. By decoupling the predictor and quantizer effect it is proved that, owing to a self-stabilization phenomenon, narrowband inputs cause local instabilities in the predictor of the jointly adaptive autoregressive moving-average-prediction/quantization used in the ADPCM 32-kb/s algorithm. Despite the assured global stability, these local instabilities are not synchronized at the encoder and its preceding decoder, and a mistracking occurs which creates quantizing noise accumulation. The tracking is then shown to be very sensitive to predictor/quantizer interaction. The discontinuities introduced in the standardized adaptive quantizer extend the mistracking problem to wideband inputs. A smoothed quantizer with reduced inauspicious interaction is proposed to remedy the problem.>

In digital adaptive echo cancellation, the sign algorithm is very attractive since it is multiplication free. However, when the residual echo undercrosses the useful signal level, the error sign is no longer significant of the canceller quality and the convergence stops. Introduction of extra noise into the error can eliminate this drawback. The system performances regarding the residual echo and the computational complexity are shown to be competitive with those of the classical gradient algorithm (not using the function sign).