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Electrical impedance spectroscopy (EIS), as an effective analytical technique for electrochemical system, has shown a wide application for food quality and safety assessment recently. Individual differences of livestock cause high variation in quality of raw meat and fish and their commercialized products. Therefore, in order to obtain the definite quality information and ensure the quality of each product, a fast and on-line detection technology is demanded to be developed to monitor product processing. EIS has advantages of being fast, nondestructive, inexpensive, and easily implemented and shows potential to develop on-line detecting instrument to replace traditional methods to realize time, cost, skilled persons saving and further quality grading. This review outlines the fundamental theories and two common measurement methods of EIS applied to biological tissue, summarizes its application specifically for quality assessment of meat and fish, and discusses challenges and future trends of EIS technology applied for meat and fish quality assessment.

One class of islanding detection methods, known as impedance measurement-based methods and voltage change monitoring-based methods, are implemented through injecting irregular currents into the network, for which reason they are defined in this paper as irregular current injection methods. This paper indicates that such methods may be affected by distributed generation (DG) unit cut-in events. Although the network impedance change can still be used as a judgment basis for islanding detection, the general impedance measurement scheme cannot separate island events from DG unit cut-in events in multi-DG operation. In view of this, this paper proposes a new islanding detection method based on an improved impedance measurement scheme, i.e., dynamic impedance measurement, which will not be affected by DG unit cut-in events and can further assist some other equipment in islanding detection. The simulations and experiments verify the stated advantages of the new islanding detection method.

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A method for realizing wavelet transform (WT) is presented, in which the WT is synthesized by a bank of switched-current (SI) filters whose impulse responses are the basic wavelet function and its dilations. SI circuits are well suitable for this application since the dilation constant across different scales of the transform can be precisely implemented and controlled by the sampling frequency. In this article, the wavelet base is approximated by a systematic algorithm with all the involved approximation parameters taken into account. Also, the SI filter employing the followthe-leader feedback (FLF) multiple-loop feedback (MLF) structure is proposed to synthesize the approximation function. The Gaussian wavelet is selected as an example to illustrate the design procedure. Simulation results indicate that the proposed method has the merits of high approximation accuracy, strong stability and low sensitivity.

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