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A new design methodology is presented for detecting spiking signals from complex brain neural potentials, which applies ultra-low-power technology to implement a nonlinear energy operator (NEO)-based spike detector. The NEO spike detector achieves a differentiator with a differential structure and a multiplier based on the dynamic translinear principle using a sub-threshold technique. As is demonstrated by the simulation results, the proposed circuit has detected the instantaneous energy of the input signals well, which focus in the range 5 Hz to 10 kHz.Introduction: Today, engaging in neuroscience research involves many domains, for example, medicine biology, microelectronics, robotics engineering, etc., among which neural signal recording is the most fundamental. Neuroscientists have implemented the possibility of using brain signals to control artificial devices, that is a prototype of a brain -machine interface (BMI) [1]. For highly-efficient and high-accuracy application of implantable BMI based on wireless transmission of information, real-time spike detection is an important requirement.Several spike detectors have been reported by researchers [2, 3], but the designs are limited to low power, low complexity and high accuracy for multichannel neural signal detection. These spike detectors have to meet several challenging performance requirements imposed by the environments of the applications. First, the detectors on the algorithms implemented in the hardware must be accurate, automatic and computationally simple. Secondly, the detectors should achieve ultra-low-power operation and operate at as low complexity as possible to reduce the size of the implantable chip. Thirdly, programmability of gain and bandwidth is necessary owing to the wide range of the neural harvest signal, since different kinds of neural signal have different signal amplitudes and frequency content.To transmit only the action potential waveforms from the frontreadout array amplifier [4] in real-time, the nonlinear energy operator (NEO) is already used to estimate the instantaneous frequency and amplitude of the signal [5]. It is also used to implement the spike detector. The NEO is defined as:

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Macroscopic tensile tests on neat PA6 and CF/PA6 prepregs showed that the cooling rate significantly affects the mechanical properties of CF/PA6 composites because of their different crystallization behaviors both at the fiber surface and in the matrix. Polarizing optical microscopy, static nanoindentation (SNI), and dynamic mechanical imaging (DMI) tests were used to characterize the anisotropic morphologies and nanomechanical performances of the interfacial characteristic regions in CF/PA6 composites at five different cooling rates. As a result, the seven interfacial characteristic regions inside the CF/PA6 composites were clearly distinguished. The interphase thickness of the CF/PA6 composites decreased with a decrease in the cooling rate. On the contrary, the interphase modulus and transcrystallinity thickness and modulus showed significant increases with a decrease in the cooling rate. The DMI and SNI test results were in agreement with each other and with the macromechanical test results. V C 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016, 133, 44106.