# Filter noise from the signal using basic thresholding
def filter_noise(self, signal):
noise_reduction_factor = np.random.uniform(0.95, 1.05) # Simulate noise filtering
filtered_signal = signal * noise_reduction_factor
print(f"Robot {self.id}: Signal filtered to {filtered_signal}")
return filtered_signal
# Amplify the signal if it"s above a certain threshold
def amplify_signal(self, signal):
amplification_factor = np.random.uniform(1.5, 2.0) # Random amplification within range
amplified_signal = signal * amplification_factor
print(f"Robot {self.id}: Amplified signal to {amplified_signal}")
return amplified_signal
# Check for cell damage and initiate repair if needed
def check_and_repair(self, signal):
if signal < 0:
self.repair_mode = True
print(f"Robot {self.id}: Damaged tissue detected, initiating repair.")
return self.perform_repair(signal)
return signal
# Perform cell repair process
def perform_repair(self, signal):
print(f"Robot {self.id}: Repairing damaged cells...")
restored_signal = np.abs(signal) + np.random.uniform(10, 20) # Restore to positive signal range
print(f"Robot {self.id}: Repair plete. Restored signal: {restored_signal}")
self.repair_mode = False
return restored_signal
# Simulation of the nanorobot handling neural signals
def run_experiment:
signal_values = np.random.uniform(-5, 10, 5) # Generate random signals with possible damage indicators
robot = NanoRobot(id=204)
for signal in signal_values:
print(f"Input signal: {signal}")
filtered_signal = robot.capture_signal(signal)
final_signal = robot.check_and_repair(filtered_signal)
print(f"Final processed signal: {final_signal}\n")
if __name__ == "__main__":
run_experiment 下面的代码注释写道:纳米机器人通过检测体内的神经信号,能够对异常或受损的信号进行捕捉和分析。首先,机器人会对神经信号进行过滤,去除噪音和干扰,从而得到更精准的神经反馈。当信号强度低于设定阈值时,机器人会自动跳过放大处理,避免错误放大损伤信号。
如果检测到异常信号,特别是负值信号,机器人会判断为细胞或组织的损伤,此时会激活“修复模式”。在修复过程中,纳米机器人利用其内置的微小设备,开始进行细胞组织的自我修复,恢复受损细胞的功能。修复完成后,机器人会重新检测信号,确保细胞恢复正常。
此外,纳米机器人还具备信号放大功能。当检测到正常但微弱的信号时,它们能够以可控的方式放大神经信号,确保神经传导的稳定性与有效性。这一系列过程不仅为生物体提供了神经保护,还进一步增强了人体对外界环境的感知能力。
正当王海洋看得入迷,听到实验室里传来声音:实验开始!