This paper describes design considerations for high frequency active BPFs up to 100 MHz. The major design issues for high frequency active filters are the excess phase shift in the integrators and high power consumption of the integrators. Typical bipolar transistor based transconductors such as the Gilbert gain cell and the linearized transconductor with two asymmetric emitter-coupled pairs have been analyzed and compared. It has been clarified that the power consumption of the linearized transconductor can be much smaller than that of the Gilbert gain cell because of its high transconductance to working current ratio while maintaining a signal to noise ratio of the same order. A simple high-speed fully differential linearized transconductor cell is proposed with emitter follower buffers and resistive loads for excess phase compensation. A novel gyrator based transformation for the LC ladder BPF has been introduced. This transformation has resulted in a structure with simple capacitor-coupled active resonators which exactly preserves the original transfer function. A fourth order 10.7 MHz BPF IC was designed using the proposed transconductors. It was fabricated and has demonstrated the usefulness of the proposed approach. In addition, an experimental 100 MHz second order BPF IC with Q=14 has been successfully implemented indicating the potential of the proposed approach.

We propose deep neural network (DNN)-based speech enhancement that reduces musical noise and achieves better auditory impressions. The musical noise is an artifact generated by nonlinear signal processing and negatively affects the auditory impressions. We aim to develop musical-noise-free speech enhancement methods that suppress the musical noise generation and produce perceptually-comfortable enhanced speech. DNN-based speech enhancement using a soft mask achieves high noise reduction but generates musical noise in non-speech regions. Therefore, first, we define kurtosis matching for DNN-based low-musical-noise speech enhancement. Kurtosis is the fourth-order moment and is known to correlate with the amount of musical noise. The kurtosis matching is a penalty term of the DNN training and works to reduce the amount of musical noise. We further extend this scheme to standardized-moment matching. The extended scheme involves using moments whose orders are higher than kurtosis and generalizes the conventional musical-noise-free method based on kurtosis matching. We formulate standardized-moment matching and explore how effectively the higher-order moments reduce the amount of musical noise. Experimental evaluation results 1) demonstrate that kurtosis matching can reduce musical noise without negatively affecting noise suppression and 2) newly reveal that the sixth-moment matching also achieves low-musical-noise speech enhancement as well as kurtosis matching.